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DTN Management Architecture

Document Type Active Internet-Draft (dtn WG)
Authors Edward J. Birrane , Sarah Heiner , Emery Annis
Last updated 2024-04-29 (Latest revision 2024-04-28)
Replaces draft-ietf-dtn-ama
RFC stream Internet Engineering Task Force (IETF)
Intended RFC status Informational
Additional resources Mailing list discussion
Stream WG state Submitted to IESG for Publication
Document shepherd Rick Taylor
Shepherd write-up Show Last changed 2023-11-10
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Delay-Tolerant Networking                                   E.J. Birrane
Internet-Draft                                               S.E. Heiner
Intended status: Informational                                  E. Annis
Expires: 30 October 2024        Johns Hopkins Applied Physics Laboratory
                                                           28 April 2024

                      DTN Management Architecture


   The Delay-Tolerant Networking (DTN) architecture describes a type of
   challenged network in which communications may be significantly
   affected by long signal propagation delays, frequent link
   disruptions, or both.  The unique characteristics of this environment
   require a unique approach to network management that supports
   asynchronous transport, autonomous local control, and a small
   footprint (in both resources and dependencies) so as to deploy on
   constrained devices.

   This document describes a DTN management architecture (DTNMA)
   suitable for managing devices in any challenged environment but, in
   particular, those communicating using the DTN Bundle Protocol (BP).
   Operating over BP requires an architecture that neither presumes
   synchronized transport behavior nor relies on query-response
   mechanisms.  Implementations compliant with this DTNMA should expect
   to successfully operate in extremely challenging conditions, such as
   over uni-directional links and other places where BP is the preferred

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
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   Drafts is at

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on 30 October 2024.

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Copyright Notice

   Copyright (c) 2024 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (
   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
   and restrictions with respect to this document.  Code Components
   extracted from this document must include Revised BSD License text as
   described in Section 4.e of the Trust Legal Provisions and are
   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Purpose . . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.3.  Organization  . . . . . . . . . . . . . . . . . . . . . .   5
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   6
   3.  Challenged Network Overview . . . . . . . . . . . . . . . . .   8
     3.1.  Challenged Network Constraints  . . . . . . . . . . . . .   8
     3.2.  Topology and Service Implications . . . . . . . . . . . .   9
       3.2.1.  Tiered Management . . . . . . . . . . . . . . . . . .  10
       3.2.2.  Remote and Local Manager Associations . . . . . . . .  11
     3.3.  Management Special Cases  . . . . . . . . . . . . . . . .  12
   4.  Desirable Design Properties . . . . . . . . . . . . . . . . .  12
     4.1.  Dynamic Architectures . . . . . . . . . . . . . . . . . .  13
     4.2.  Hierarchically Modeled Information  . . . . . . . . . . .  13
     4.3.  Adaptive Push of Information  . . . . . . . . . . . . . .  14
     4.4.  Efficient Data Encoding . . . . . . . . . . . . . . . . .  15
     4.5.  Universal, Unique Data Identification . . . . . . . . . .  15
     4.6.  Runtime Data Definitions  . . . . . . . . . . . . . . . .  16
     4.7.  Autonomous Operation  . . . . . . . . . . . . . . . . . .  17
   5.  Current Remote Management Approaches  . . . . . . . . . . . .  18
     5.1.  SNMP and SMI Models . . . . . . . . . . . . . . . . . . .  19
       5.1.1.  The SMI Modeling Language . . . . . . . . . . . . . .  19
       5.1.2.  SNMP Protocol and Transport . . . . . . . . . . . . .  20
     5.2.  XML-Infoset-Based Protocols and YANG Models . . . . . . .  20
       5.2.1.  The YANG Modeling Language  . . . . . . . . . . . . .  20
       5.2.2.  NETCONF Protocol and Transport  . . . . . . . . . . .  22
       5.2.3.  RESTCONF Protocol and Transport . . . . . . . . . . .  23
       5.2.4.  CORECONF Protocol and Transport . . . . . . . . . . .  23
     5.3.  gRPC Network Management Interface (gNMI)  . . . . . . . .  23
       5.3.1.  The Protobuf Modeling Language  . . . . . . . . . . .  24
       5.3.2.  gRPC Protocol and Transport . . . . . . . . . . . . .  24
     5.4.  Intelligent Platform Management Interface (IPMI)  . . . .  24

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     5.5.  Autonomic Networking  . . . . . . . . . . . . . . . . . .  24
     5.6.  Deep Space Autonomy . . . . . . . . . . . . . . . . . . .  25
   6.  Motivation for New Features . . . . . . . . . . . . . . . . .  25
   7.  Reference Model . . . . . . . . . . . . . . . . . . . . . . .  26
     7.1.  Important Concepts  . . . . . . . . . . . . . . . . . . .  26
     7.2.  Model Overview  . . . . . . . . . . . . . . . . . . . . .  27
     7.3.  Functional Elements . . . . . . . . . . . . . . . . . . .  28
       7.3.1.  Managed Applications and Services . . . . . . . . . .  28
       7.3.2.  DTNMA Agent (DA)  . . . . . . . . . . . . . . . . . .  29
       7.3.3.  Managing Applications and Services  . . . . . . . . .  31
       7.3.4.  DTNMA Manager (DM)  . . . . . . . . . . . . . . . . .  32
       7.3.5.  Pre-Shared Definitions  . . . . . . . . . . . . . . .  34
   8.  Desired Services  . . . . . . . . . . . . . . . . . . . . . .  34
     8.1.  Local Monitoring and Control  . . . . . . . . . . . . . .  35
     8.2.  Local Data Fusion . . . . . . . . . . . . . . . . . . . .  35
     8.3.  Remote Configuration  . . . . . . . . . . . . . . . . . .  36
     8.4.  Remote Reporting  . . . . . . . . . . . . . . . . . . . .  36
     8.5.  Authorization . . . . . . . . . . . . . . . . . . . . . .  37
   9.  Logical Autonomy Model  . . . . . . . . . . . . . . . . . . .  37
     9.1.  Overview  . . . . . . . . . . . . . . . . . . . . . . . .  38
     9.2.  Model Characteristics . . . . . . . . . . . . . . . . . .  40
     9.3.  Data Value Representation . . . . . . . . . . . . . . . .  42
     9.4.  Data Reporting  . . . . . . . . . . . . . . . . . . . . .  42
     9.5.  Command Execution . . . . . . . . . . . . . . . . . . . .  43
     9.6.  Predicate Autonomy Rules  . . . . . . . . . . . . . . . .  44
   10. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .  44
     10.1.  Notation . . . . . . . . . . . . . . . . . . . . . . . .  44
     10.2.  Serialized Management  . . . . . . . . . . . . . . . . .  45
     10.3.  Intermittent Connectivity  . . . . . . . . . . . . . . .  46
     10.4.  Open-Loop Reporting  . . . . . . . . . . . . . . . . . .  48
     10.5.  Multiple Administrative Domains  . . . . . . . . . . . .  49
     10.6.  Cascading Management . . . . . . . . . . . . . . . . . .  51
   11. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  53
   12. Security Considerations . . . . . . . . . . . . . . . . . . .  53
   13. Informative References  . . . . . . . . . . . . . . . . . . .  53
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .  59
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  59

1.  Introduction

   This document describes a logical, informational DTN management
   architecture (DTNMA) suitable for operating devices in a challenged
   architecture - such as those communicating using the DTN Bundle
   Protocol (BPv7) [RFC9171].

   Challenged networks have certain properties that differentiate them
   from other kinds of networks.  These properties, outlined in
   Section 2.2.1 of [RFC7228], include lacking end-to-end IP

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   connectivity, having "serious interruptions" to end-to-end
   connectivity, and exhibiting delays longer than can be tolerated by
   end-to-end synchronization mechanisms (such as TCP).

   These challenged properties can be caused by a variety of factors
   such as physical constraints (e.g., long signal propagation delays
   and frequent link disruptions), administrative policies (e.g.,
   quality-of-service prioritization, service-level agreements, and
   traffic management and scheduling), and off-nominal behaviors (e.g.,
   active attackers and misconfigurations).  Since these challenges are
   not solely caused by sparseness, instances of challenged networks
   will persist even in increasingly connected environments.

   The Delay-Tolerant Networking (DTN) architecture, described in
   [RFC4838], has been designed for data exchange in challenged
   networks.  Just as the DTN architecture requires new capabilities for
   transport and transport security, special consideration is needed for
   the operation of devices in a challenged network.

1.1.  Purpose

   This document describes how challenged network properties affect the
   operation of devices in those networks.  This description is
   presented as a logical architecture formed from a union of best
   practices for operating devices deployed in challenged environments.

   One important practice captured in this document is the concept of
   self-operation.  Self-operation involves operating a device without
   human interactivity, without system-in-the-loop synchronous function,
   and without a synchronous underlying transport layer.  This means
   that devices determine their own schedules for data reporting, their
   own operational configuration, and perform their own error discovery
   and mitigation.

1.2.  Scope

   This document includes the information necessary to document existing
   practices for operating devices in a challenged network in the
   context of a logical architecture.  A logical architecture describes
   the logical operation of a system by identifying components of the
   system (such as in a reference model), the behaviors they enable, and
   use cases describing how those behaviors result in the desired
   operation of the system.

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   Logical architectures are not functional architectures.  Therefore,
   any functional design for achieving desired behaviors is out of scope
   for this document.  The set of architectural principles presented
   here is not meant to completely specify interfaces between

   The selection of any particular transport or network layer is outside
   of the scope of this document.  The DTNMA does not require the use of
   any specific protocol such as IP, BP, TCP, or UDP.  In particular,
   the DTNMA design does not presume the use of BPv7, IPv4 or IPv6.

      |  NOTE: As BPv7 is the preferred transport for networks
      |  conforming to the DTN architecture, the DTNMA should be
      |  considered for any BPv7 network deployment.  However, the DTNMA
      |  may also be used in other networks that have similar needs for
      |  this particular style of self-operation.  For this reason, the
      |  DTNMA does not require the use of BPv7 to transport management
      |  information.

   Network features such as naming, addressing, routing, and
   communications security are out of scope of the DTNMA.  It is
   presumed that any operational network communicating DTNMA messages
   would implement these services for any payloads carried by that

   The interactions between and amongst the DTNMA and other management
   approaches are outside of the scope of this document.

1.3.  Organization

   The remainder of this document is organized into the following nine
   sections, described as follows.

   Terminology:  This section identifies terms fundamental to
      understanding DTNMA concepts.  Whenever possible, these terms
      align in both word selection and meaning with their use in other
      management protocols.

   Challenged Network Overview:  This section describes important
      aspects of challenged networks and necessary approaches for their

   Desirable Design Properties:  This section defines those properties
      of the DTNMA needed to operate within the constraints of a
      challenged network.  These properties are similar to the
      specification of system-level requirements of a DTN management

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   Current Remote Management Approaches:  This section provides a brief
      overview of existing remote management approaches.  Where
      possible, the DTNMA adopts concepts from these approaches.

   Motivation for New Features:  This section provides an overall
      motivation for this work, to include explaining why a management
      architecture for challenged networks is useful and necessary.

   Reference Model:  This section defines a reference model that can be
      used to reason about the DTNMA independent of an implementation or
      implementation architecture.  This model identifies the logical
      components of the system and the high-level relationships and
      behaviors amongst those components.

   Desired Services:  This section identifies and defines the DTNMA
      services provided to network and mission operators.

   Logical Autonomy Model:  This section provides an exemplar data model
      that can be used to reason about DTNMA control and data flows.
      This model is based on the DTNMA reference model.

   Use Cases:  This section presents multiple use cases accommodated by
      the DTNMA architecture.  Each use case is presented as a set of
      control and data flows referencing the DTNMA reference model and
      logical autonomy model.

2.  Terminology

   This section defines terminology that either is unique to the DTNMA
   or is necessary for understanding the concepts defined in this

   Timely Data Exchange:  The ability to communicate information between
      two (or more) entities within a required period of time.  In some
      cases, a 1-second exchange may not be timely and in other cases
      1-hour exchange may be timely.

   Local Operation:  The operation of a device by an application co-
      resident on that device.  Local operators are applications running
      on a device, and there might be one or more of these applications
      working independently or as one to perform the local operations
      function.  Absent error conditions, local operators are always
      expected to be available to the devices they manage.

   Remote Operation:  The operation of a device by an application
      running on a separate device.  Remote operators communicate with
      operated devices over a network.  Remote operators are not always
      expected to be availabe to the devices they operate.

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   DTN Management:  The management, monitoring, and control of a device
      that does not depend on stateful connections, timely data exchange
      of management messages, or system-in-the-loop synchronous
      functions.  DTN management is accomplished as a fusion of local
      operation and remote operation techniques; remote operators manage
      the configuration of local operators who provide monitoring and
      control of their co-resident devices.

   DTNMA Agent (DA):  A role associated with a managed device,
      responsible for reporting performance data, accepting policy
      directives, performing autonomous local control, error-handling,
      and data validation.  DAs exchange information with DMs operating
      either on the same device and/or on remote devices in the network.
      A DA is a type of local operator.

   DTNMA Manager (DM):  A role associated with a managing device
      responsible for configuring the behavior of, and eventually
      receiving information from, DAs.  DMs interact with one or more
      DAs located on the same device and/or on remote devices in the
      network.  A DM is a type of remote operator.

   Controls:  Procedures run by a DA to change the behavior,
      configuration, or state of an application or protocol managed by
      that DA.  This includes procedures to manage the DA itself, such
      as to have the DA produce performance reports or to apply new
      management policies.

   Externally Defined Data (EDD):  Typed information made available to a
      DA by its hosting device, but not computed directly by the DA

   Data Reports:  Typed, ordered collections of data values gathered by
      one or more DAs and provided to one or more DMs.  Reports comply
      to the format of a given Data Report Schema.

   Data Report Schemas:  Named, ordered collection of data elements that
      represent the schema of a Data Report.

   Rules:  Unit of autonomous specification that provides a stimulus-
      response relationship between time or state on a DA and the
      actions or operations to be run as a result of that time or state.

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3.  Challenged Network Overview

   The DTNMA provides network management services able to operate in a
   challenged network environment, such as envisioned by the DTN
   architecture.  This section describes what is meant by the term
   "challenged network", the important properties of such a network, and
   observations on impacts to management approaches.

3.1.  Challenged Network Constraints

   Constrained networks are defined as networks where "some of the
   characteristics pretty much taken for granted with link layers in
   common use in the Internet at the time of writing are not
   attainable."  [RFC7228].  This broad definition captures a variety of
   potential issues relating to physical, technical, and regulatory
   constraints on message transmission.  Constrained networks typically
   include nodes that regularly reboot or are otherwise turned off for
   long periods of time, transmit at low or asynchronous bitrates, and/
   or have very limited computational resources.

   Separately, a challenged network is defined as one that "has serious
   trouble maintaining what an application would today expect of the
   end-to-end IP model" [RFC7228].  Links in such networks may be
   impacted by attenuation, propagation delays, mobility, occultation,
   and other limitations imposed by energy and mass considerations.
   Therefore, systems relying on such links cannot guarantee timely end-
   to-end data exchange.

      |  NOTE: Because challenged networks might not provide services
      |  expected of the end-to-end IP model, devices in such networks
      |  might not implement networking stacks associated with the end-
      |  to-end IP model.  This means that devices might not include
      |  support for certain transport protocols (TCP/QUIC/UDP), web
      |  protocols (HTTP), or internetworking protocols (IPv4/IPv6).

   By these definitions, a "challenged" network is a special type of
   "constrained" network, where constraints prevent timely end-to-end
   data exchange.  As such, "all challenged networks are constrained
   networks ... but not all constrained networks are challenged networks
   ...  Delay-Tolerant Networking (DTN) has been designed to cope with
   challenged networks" [RFC7228].

   Solutions that work in constrained networks might not be solutions
   that work in challenged networks.  In particular, challenged networks
   exhibit the following properties that impact the way in which the
   function of network management is considered.

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   *  Timely end-to-end data exchange cannot be guaranteed to exist at
      any given time between any two nodes.

   *  Latencies on the order of seconds, hours, or days must be

   *  Managed devices cannot be guaranteed to always be powered so as to
      receive ad-hoc management requests (even requests with
      artificially extended timeout values).

   *  Individual links may be uni-directional.

   *  Bi-directional links may have asymmetric data rates.

   *  The existence of external infrastructure, services, systems, or
      processes such as a Domain Name Service (DNS) or a Certificate
      Authority (CA) cannot be guaranteed.

3.2.  Topology and Service Implications

   The set of constraints that might be present in a challenged network
   impact both the topology of the network and the services active
   within that network.

   Operational networks handle cases where nodes join and leave the
   network over time.  These topology changes may or may not be planned,
   they may or may not represent errors, and they may or may not impact
   network services.  Challenged networks differ from other networks not
   in the presence of topological change, but in the likelihood that
   impacts to topology result in impacts to network services.

   The difference between topology impacts and service impacts can be
   expressed in terms of connectivity.  Topological connectivity usually
   refers to the existence of a path between an application message
   source and destination.  Service connectivity, alternatively, refers
   to the existence of a path between a node and one or more services
   needed to process (often just-in-time) application messaging.
   Examples of service connectivity include access to infrastructure
   services such as a Domain Name System (DNS) or a Certificate
   Authority (CA).

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   In networks that might be partitioned most of the time, it is less
   likely that a node would concurrently access both an application
   endpoint and one or more network service endpoints.  For this reason,
   network services in a challenged network should be designed to allow
   for asynchronous operation.  Accommodating this use case often
   involves the use of local caching, pre-placing information, and not
   hard-coding message information at a source that might change when a
   message reaches its destination.

      |  NOTE: One example of rethinking services in a challenged
      |  network is the securing of BPv7 bundles.  The BPSec [RFC9172]
      |  security extensions to BPv7 do not encode security destinations
      |  when applying security.  Instead, BPSec requires nodes in a
      |  network to identify themselves as security verifiers or
      |  acceptors when receiving and processing secured messages.

3.2.1.  Tiered Management

   Network operations and management approaches need to adapt to the
   topology and service impacts encountered in challenged networks.  In
   particular, the roles and responsibilities of "managers" and "agents"
   need to be different than what would be expected of unchallenged

   When connectivity to a manager cannot be guaranteed, agents will need
   to rely on locally available information and local autonomy to react
   to changes at the node.  When an agent uses local autonomy for self-
   operation, it acts as a local operator serving as a proxy for an
   absent remote operator.

   Therefore, the role of a "manager" must become one of a remote
   operator generating configurations and other essential updates for
   the local operator "agents" that are co-resident on a managed device.

   This approach creates a two-tiered management architecture.  The
   first tier is the management of the local operator configuration
   using any one of a variety of standard mechanisms, models, and
   protocols.  The second tier is the operation of the local device
   through the local operator.

   The DTNMA defines the DTNMA Manager (DM) as a remote operator
   application and the DTNMA Agent (DA) as an agent acting as a local
   operator application.  In this model, which is illustrated in
   Figure 1, the DM and DA can be viewed as applications with the DM
   producing new configurations and the DA receiving those
   configurations from an underlying management mechanism.

   Two-Tiered Management Architecture

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        / +------------+           +-----------+    Local    +---------+
  TIER /  | DM (Remote |           | DA (Local |  Operation  | Managed |
   2   \  |  Operator) |           | Operator) | <---------> |   Apps  |
  MGMT  \ +------------+           +-----------+             +---------+
         \_      ^                        ^
                 | configs                | configs
          _      |                        |
         /       V                        V
        / +------------+    Remote    +------------+
  TIER /  | Management |  Management  | Management |
   1   \  |   Client   | <----------> |   Server   |
  MGMT  \ +------------+              +------------+

                                 Figure 1

   In this approach, the configurations produced by the DM are based on
   the DA features and associated data model.  How those configurations
   are transported between the DM and the DA, and how results are
   communicated back from the DA to the DM, can be accomplished using
   whatever mechanism is most appropriate for the network and the device
   platforms.  For example, the use of a NETCONF, RESTCONF, or SNMP
   server on the managed device to provide configurations to a DA.

3.2.2.  Remote and Local Manager Associations

   In addition to disconnectivity, topological change can alter the
   associations amongst managed and managing devices.  Different
   managing devices might be active in a network at different times or
   in different partitions.  Managed devices might communicate with
   some, all, or none of these managing devices as a function of their
   own local configuration and policy.

      |  NOTE: These concepts relate to practices in conventional
      |  networks.  For example, supporting multiple managing devices is
      |  similar to deploying multiple instances of a network service --
      |  such as a DNS server or CA node.  Selecting from a set of
      |  managing devices is similar to a sensor node practice of
      |  electing cluster heads to act as privileged nodes for data
      |  storage and exfiltration.

   Therefore, a network management architecture for challenged networks

   1.  Support a many-to-many association amongst managing and managed
       devices, and

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   2.  Allow "control from" and "reporting to" managing devices to
       function independent of one another.

3.3.  Management Special Cases

   The following special cases illustrate some of the operational
   situations that can be encountered in the management of devices in a
   challenged network.

   One-Way Management:  A managed device can only be accessed via a uni-
      directional link, or a via a link whose duration is shorter than a
      single round-trip propagation time.  Results of this management
      may come back at a different time, over a different path, and/or
      as observable from out-of-band changes to device behavior.

   Summary Data:  A managing device might only receive summary data of a
      managed device's state because a link or path is constrained by
      capacity or reliability.

   Bulk Historical Reporting:  A managing device receives a large volume
      of historical report data for a managed device.  This can occur
      when a managed device rejoins a network or has temporary access to
      a high capacity link (or path) to the managed device.

   Multiple Managers  A managed device tracks multiple managers in the
      network and communicates with them as a function of time, local
      state, or network topology.  This includes challenged networks
      that interconnect two or more unchallenged networks such that
      managed and managing devices exist in different networks.

   These special cases highlight the need for managed devices to operate
   without presupposing a dedicated connection to a single managing
   device.  Managing devices in a challenged network might never expect
   a reply to a command, and communications from managed devices may be
   delivered much later than the events being reported.

4.  Desirable Design Properties

   This section describes those design properties that are desirable
   when defining a management architecture operating across challenged
   links in a network.  These properties ensure that network management
   capabilities are retained even as delays and disruptions in the
   network scale.  Ultimately, these properties are the driving design
   principles for the DTNMA.

      |  NOTE: These properties may influence the design, construction,
      |  and adaptation of existing management tools for use in
      |  challenged networks.  For example, the properties of the DTN

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      |  architecture [RFC4838] resulted in the development of BPv7
      |  [RFC9171] and BPSec [RFC9172].  The DTNMA may result in the
      |  construction of new management data models, policy expressions,
      |  and/or protocols.

4.1.  Dynamic Architectures

   The DTNMA should be agnostic of the underlying physical topology,
   transport protocols, security solutions, and supporting
   infrastructure of a given network.  Due to the likelihood of
   operating in a frequently partitioned environment, the topology of a
   network may change over time.  Attempts to stabilize an architecture
   around individual nodes can result in a brittle management framework
   and the creation of congestion points during periods of connectivity.

   The DTNMA should not prescribe any association between a DM and a DA
   other than those defined in this document.  There should be no
   logical limitation to the number of DMs that can control a DA, the
   number of DMs that a DA should report to, or any requirement that a
   DM and DA relationship implies a pair.

      |  NOTE: Practical limitations on the relationships between and
      |  amongst DMs and DAs will exist as a function of the
      |  capabilities of networked devices.  These limitations derive
      |  from processing and storage constraints, performance
      |  requirements, and other engineering factors.  While this
      |  information is vital to the proper engineering of a managed and
      |  managing device, they are implementation considerations, and
      |  not otherwise design constraints on the DTNMA.

4.2.  Hierarchically Modeled Information

   The DTNMA should use data models to define the syntactic and semantic
   contracts for data exchange between a DA and a DM.  A given model
   should have the ability to "inherit" the contents of other models to
   form hierarchical data relationships.

      |  NOTE: The term data model in this context refers to a schema
      |  that defines a contract between a DA and a DM for how
      |  information is represented and validated.

   Many network management solutions use data models to specify the
   semantic and syntactic representation of data exchanged between
   managed and managing devices.  The DTNMA is not different in this
   regard - information exchanged between DAs and DMs should conform to
   one or more pre-defined, normative data models.

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   A common best practice when defining a data model is to make it
   cohesive.  A cohesive model is one that includes information related
   to a single purpose such as managing a single application or
   protocol.  When applying this practice, it is not uncommon to develop
   a large number of small data models that, together, describe the
   information needed to manage a device.

   Another best practice for data model development is the use of
   inclusion mechanisms to allow one data model to include information
   from another data model.  This ability to include a data model avoids
   repeating information in different data models.  When one data model
   includes information from another data model, there is an implied
   model hierarchy.

   Data models in the DTNMA should allow for the construction of both
   cohesive models and hierarchically related models.  These data models
   should be used to define all sources of information that can be
   retrieved, configured, or executed in the DTNMA.  This includes
   supporting DA autonomy functions such as parameterization, filtering,
   and event driven behaviors.  These models will be used to both
   implement interoperable autonomy engines on DAs and define
   interoperable report parsing mechanisms on DMs.

      |  NOTE: While data model hierarchies can result in a more concise
      |  data model, arbitrarily complex nesting schemes can also result
      |  in very verbose encodings.  Where possible, data identification
      |  schemes should be constructed that allow for both hierarchical
      |  data and highly compressible data identification.

4.3.  Adaptive Push of Information

   DAs in the DTNMA architecture should determine when to push
   information to DMs as a function of their local state.

   Pull management mechanisms require a managing device to send a query
   to a managed device and then wait for a response to that specific
   query.  This practice implies some knowledge synchronization between
   entities (which may be as simple as knowing when a managed device
   might be powered).  However, challenged networks cannot guarantee
   timely round-trip data exchange.  For this reason, pull mechanisms
   should be avoided in the DTNMA.

   Push mechanisms, in this context, refer to the ability of DAs to
   leverage local autonomy to determine when and what information should
   be sent to which DMs.  The push is considered adaptive because a DA
   determines what information to push (and when) as an adaptation to
   changes to the DA's internal state.  Once pushed, information might
   still be queued pending connectivity of the DA to the network.

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      |  NOTE: Even in cases where a round-trip exchange can occur, pull
      |  mechanisms increase the overall amount of traffic in the
      |  network and preclude the use of autonomy at managed devices.
      |  So even when pull mechanisms are feasible they should not be
      |  considered a pragmatic alternative to push mechanisms.

4.4.  Efficient Data Encoding

   Messages exchanged between a DA and a DM in the DTNMA should be
   defined in a way that allows for efficient on-the-wire encoding.
   DTNMA design decisions that result in smaller message sizes should be
   preferred over those that result in larger message sizes.

   There is a relationship between message encoding and message
   processing time at a node.  Messages with little or no encodings may
   simplify node processing whereas more compact encodings may require
   additional activities to generate/parse encoded messages.  Generally,
   compressing a message takes processing time at the sender and
   decompressing a message takes processing time at a receiver.
   Therefore, there is a design tradeoff between minimizing message
   sizes and minimizing node processing.

   There is a significant advantage to smaller DTNMA message sizes in a
   challenged network.  Smaller messages require smaller periods of
   viable transmission for communication, they incur less re-
   transmission cost, and they consume less resources when persistently
   stored en-route in the network.

      |  NOTE: Naive approaches to minimizing message size through
      |  general purpose compression algorithms do not produce minimal
      |  encodings.  Data models can, and should, be designed for
      |  compact encoding from the beginning.  Design strategies for
      |  compact encodings involve using structured data, hierarchical
      |  data models, and common sub-structures within data models.
      |  These strategies allow for compressibility beyond what would
      |  otherwise be achieved by computing large hash values over
      |  generalized data structures.

4.5.  Universal, Unique Data Identification

   Data elements within the DTNMA should be uniquely identifiable so
   that they can be individually manipulated.  Further, these
   identifiers should be universal - the identifier for a data element
   should be the same regardless of role, implementation, or network

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   Identification schemes that would be relative to a specific DA or
   specific system configuration might change over time and should be
   avoided.  Relying on relative identification schemes would require
   resynchronizing relative state when nodes in a challenge network
   reconnect after periods of partition.  This type of resynchronization
   should be avoided whenever possible.

      |  NOTE: Consider a common management technique for approximating
      |  an associative array lookup.  If a managed device tracks the
      |  number of bytes passed by multiple named interfaces, then the
      |  number of bytes through a specific named interface ("int_foo"),
      |  would be retrieved in the following way:
      |     1.  Query a list of ordered interface names from an agent.
      |     2.  Find the name that matches "int_foo" and infer the
      |         agent's index of "int_foo" from the ordered interface
      |         list.  In this instance, assume "int_foo" is the 4th
      |         interface in the list.
      |     3.  Query the agent (again) to now return the number of
      |         bytes passed through the 4th interface.
      |  Ignoring the inefficiency of two round-trip exchanges, this
      |  mechanism will fail if an agent implementation changes its
      |  index mapping between the first and second query.
      |  The desired data being queried, "number of bytes through
      |  int_foo" should be uniquely and universally identifiable and
      |  independent of how that data exists in any agent's custom
      |  implementation.

4.6.  Runtime Data Definitions

   The DTNMA allows for the addition of new data elements to a data
   model as part of the runtime operation of the management system.
   These definitions may represent custom data definitions that are
   applicable only for a particular device or network.  Custom
   definitions should also be able to be removed from the system during

   The goal of this approach is to dynamically add or remove data
   elements to the local runtime schemas as needed - such as the
   definition of new counters, new reports, or new rules.

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   The custom definition of new data from existing data (such as through
   data fusion, averaging, sampling, or other mechanisms) provides the
   ability to communicate desired information in as compact a form as

      |  NOTE: A DM could, for example, define a custom data report that
      |  includes only summary information around a specific operational
      |  event or as part of specific debugging.  DAs could then produce
      |  this smaller report until it is no longer necessary, at which
      |  point the custom report could be removed from the management
      |  system.

   Custom data elements should be calculated and used both as parameters
   for DA autonomy and for more efficient reporting to DMs.  Defining
   new data elements allows for DAs to perform local data fusion and
   defining new reporting templates allows for DMs to specify desired
   formats and generally save on link capacity, storage, and processing

4.7.  Autonomous Operation

   The management of applications by a DA should be achievable using
   only knowledge local to the DA because DAs might need to operate
   during times when they are disconnected from a DM.

   DA autonomy may be used for simple automation of predefined tasks or
   to support semi-autonomous behavior in determining when to run tasks
   and how to configure or parameterize tasks when they are run.

   Important features provided by the DA are listed below.  These
   features work together to accomplish tasks.  As such, there is
   commonality amongst their definitions and nature of their benefits.

   Stand-alone Operation:  Pre-configuration allows DAs to operate
      without regular contact with other nodes in the network.  Updates
      for configurations remain difficult in a challenged network, but
      this approach removes the requirement that a DM be in-the-loop
      during regular operations.  Preconfiguring stimuli-and-responses
      on a DA during periods of connectivity allows DAs to self-manage
      during periods of disconnectivity.

   Deterministic Behavior:  Operational systems might need to act in a
      deterministic way even in the absence of an operator in-the-loop.
      Deterministic behavior allows an out-of-contact DM to predict the
      state of a DA and to determine how a DA got into a particular

   Engine-Based Behavior:  Operational systems might not be able to

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      deploy "mobile code" [RFC4949] solutions due to network bandwidth,
      memory or processor loading, or security concerns.  Engine-based
      approaches provide configurable behavior without incurring these

   Authorization and Accounting:  The DTNMA does not require a specific
      underlying transport protocol, network infrastructure, or network
      services.  Therefore, mechanisms for authorization and accounting
      need to be present in a standard way at DAs and DMs to provide
      these functions if the underlying network does not.  This is
      particularly true in cases where multiple DMs may be active
      concurrently in the network.

   To understand the contributions of these features to a common
   behavior, consider the example of a managed device coming online with
   a set of pre-installed configuration.  In this case, the device's
   stand-alone operation comes from the pre-configuration of its local
   autonomy engine.  This engine-based behavior allows the system to
   behave in a deterministic way and any new configurations will need to
   be authorized before being adopted.

   Features such as deterministic processing and engine-based behavior
   are separate from (but do not preclude the use of) other Artificial
   Intelligence (AI) and Machine Learning (ML) approaches for device

5.  Current Remote Management Approaches

   Several remote management solutions have been developed for both
   local-area and wide-area networks.  Their capabilities range from
   simple configuration and report generation to complex modeling of
   device settings, state, and behavior.  Each of these approaches are
   successful in the domains for which they have been built, but are not
   all equally functional when deployed in a challenged network.

   This section describes some of the well-known protocols for remote
   management and contrasts their purposes with the desirable properties
   of the DTNMA.  The purpose of this comparison is to identify parts of
   existing approaches that can be adopted or adapted for use in
   challenged networks and where new capabilities should be created
   specifically for this environment.

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5.1.  SNMP and SMI Models

   An early and widely used example of a remote management protocol is
   the Simple Network Management Protocol (SNMP) currently at Version 3
   [RFC3410].  The SNMP utilizes a request/response model to get and set
   data values within an arbitrarily deep object hierarchy.  Objects are
   used to identify data such as host identifiers, link utilization
   metrics, error rates, and counters between application software on
   managing and managed devices [RFC3411].  Additionally, SNMP supports
   a model for unidirectional push messages, called event notifications,
   based on agent-defined triggering events.

   SNMP relies on logical sessions with predictable round-trip latency
   to support its "pull" mechanism but a single activity is likely to
   require many round-trip exchanges.  Complex management can be
   achieved, but only through careful orchestration of real-time, end-
   to-end, managing-device-generated query-and-response logic.

   There is existing work that uses the SNMP data model to support some
   low-fidelity Agent-side processing, to include the Distributed
   Management Expression MIB [RFC2982] and Definitions of Managed
   Objects for the Delegation of Management Scripts [RFC3165].  However,
   Agent autonomy is not an SNMP mechanism, so support for a local agent
   response to an initiating event is limited.  In a challenged network
   where the delay between a managing device receiving an alert and
   sending a response can be significant, SNMP is insufficient for
   autonomous event handling.

5.1.1.  The SMI Modeling Language

   SNMP separates the representations for managed data models from
   Manager--Agent messaging, sequencing and encoding.  Each data model
   is termed a Management Information Base (MIB) [RFC3418] and uses the
   Structure of Management Information (SMI) modeling language
   [RFC2578].  Additionally, the SMI itself is based on the ASN.1 Syntax
   [ASN.1] which is used not just for SMI but for other, unrelated data
   structure specification such as the Cryptographic Message Syntax
   (CMS) [RFC5652].  Separating data models from messaging and encoding
   is a best practice in remote management protocols and is also
   necessary for the DTNMA.

   Each SNMP MIB is composed of managed object definitions each of which
   is associated with a hierarchical Object Identifier (OID).  Because
   of the arbitrarily deep nature of MIB object trees, the size of OIDs
   is not strictly bounded by the protocol (though may be bounded by

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5.1.2.  SNMP Protocol and Transport

   The SNMP protocol itself, which is at version 2 [RFC3416], can
   operate over a variety of transports, including plaintext UDP/IP
   [RFC3417], SSH/TCP/IP [RFC5592], and DTLS/UDP/IP or TLS/TCP/IP

   SNMP uses an abstracted security model to provide authentication,
   integrity, and confidentiality.  There are options for user-based
   security model (USM) of [RFC3414], which uses in-message security,
   and transport security model (TSM) [RFC5591], which relies on the
   transport to provide security functions and interfaces.

5.2.  XML-Infoset-Based Protocols and YANG Models

   Several network management protocols, including NETCONF [RFC6241],
   RESTCONF [RFC8040], and CORECONF [I-D.ietf-core-comi], share the same
   XML information set [xml-infoset] for its hierarchical managed
   information and [XPath] expressions to identify nodes of that
   information model.  Since they share the same information model and
   the same data manipulation operations, together they will be referred
   to as "*CONF" protocols.  Each protocol, however, provides a
   different encoding of that information set and its related operation-
   specific data.

   The YANG modeling language of [RFC7950] is used to define the data
   model for these management protocols.  Currently, YANG represents the
   IETF standard for defining managed information models.

5.2.1.  The YANG Modeling Language

   The YANG modeling language defines a syntax and modular semantics for
   organizing and accessing a device's configuration or operational
   information.  YANG allows subdividing a full managed configuration
   into separate namespaces defined by separate YANG modules.  Once a
   module is developed, it is used (directly or indirectly) on both the
   client and server to serve as a contract between the two.  A YANG
   module can be complex, describing a deeply nested and inter-related
   set of data nodes, actions, and notifications.

   Unlike the separation in Section 5.1.1 between ASN.1 syntax and
   module semantics from higher-level SMI data model semantics, YANG
   defines both a text syntax and module semantics together with data
   model semantics.

   The YANG language provides flexibility in the organization of model
   objects to the model developer.  The YANG supports a broad range of
   data types noted in [RFC6991].  YANG supports the definition of

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   parameterized Remote Procedure Calls (RPCs) and actions to be
   executed on managed devices as well as the definition of event
   notifications within the model.

      |  Current *CONF notification logic allows a client to subscribe
      |  to the delivery of specific containers or data nodes defined in
      |  the model, either on a periodic or "on change" basis [RFC8641].
      |  These notification events can be filtered according to XPath
      |  [XPath] or subtree [RFC6241] filtering as described in
      |  Section 2.2 of [RFC8639].

   The use of YANG for data modeling necessarily comes with some side-
   effects, some of which are described here.

   Text Naming:  Data nodes, RPCs, and notifications within a YANG model
      are named by a namespace-qualified, text-based path of the module,
      sub-module, container, and any data nodes such as lists, leaf-
      lists, or leaves, without any explicit hierarchical organization
      based on data or object type.

      Existing efforts to make compressed names for YANG objects, such
      as the YANG Schema Item iDentifiers (SID) from Section 3.2 of
      [RFC9254], allow a node to be named by an globally unique integer
      value but are still relatively verbose (up to 8 bytes per item)
      and still must be translated into text form for things like
      instance identification (see below).  Additionally, when
      representing a tree of named instances the child elements can use
      differential encoding of SID integer values as "delta" integers.
      The mechanisms for assigning SIDs and the lifecycle of those SIDs
      are still in development [I-D.ietf-core-sid].

   Text Values and Built-In Types:  Because the original use of YANG
      with NETCONF was to model XML information sets, the values and
      built-in types are necessarily text based.  The JSON encoding of
      YANG data [RFC7951] allows for optimized representations of many
      built-in types, and similarly the CBOR encoding [RFC9254] allows
      for different optimized representations.

      In particular, the YANG built-in types natively support a fixed
      range of decimal fractions (Section 9.3 of [RFC7950]) but
      purposefully do not support floating point numbers.  There are
      alternatives, such as the type bandwidth-ieee-float32 from
      [RFC8294] or using the "binary" type with one of the IEEE-754

   Deep Hierarchy:  YANG allows for, and current YANG modules take

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      advantage of, the ability to deeply nest a model hierarchy to
      represent complex combinations and compositions of data nodes.
      When a model uses a deep hierarchy of nodes this necessarily means
      that the qualified paths to name those nodes and instances is
      longer than a flat hierarchy would be.

   Instance Identification:  The node instances in a YANG module
      necessarily use XPath expressions for identification.  Some
      identification is constrained to be strictly within the YANG
      domain, such as "must" "when", "augment", or "deviation"
      statements.  Other identification needs to be processed by a
      managed device, such as in "instance-identifier" built-in type.
      This means any implementation of a managed device must include
      XPath processing and related information model handling of
      Section 6.4 of [RFC7950] and its referenced documents.

   Protocol Coupling:  A significant amount of existing YANG tooling or
      modeling presumes the use of YANG data within a management
      protocol with specific operations available.  For example, the
      access control model of [RFC8341] relies on those operations
      specific to the *CONF protocols for proper behavior.

      The emergence of multiple NETCONF-derived protocols may make these
      presumptions less problematic in the future.  Work to more
      consistently identify different types of YANG modules and their
      use has been undertaken to disambiguate how YANG modules should be
      treated [RFC8199].

   Manager-Side Control:  YANG RPCs and actions execute on a managed
      device and generate an expected, structured response.  RPC
      execution is strictly limited to those issued by the manager.
      Commands are executed immediately and sequentially as they are
      received by the managed device, and there is no method to
      autonomously execute RPCs triggered by specific events or

   The YANG modeling language continues to evolve as new features are
   needed by adopting management protocols.

5.2.2.  NETCONF Protocol and Transport

   NETCONF is a stateful, XML-encoding-based protocol that provides a
   syntax to retrieve, edit, copy, or delete any data nodes or exposed
   functionality on a server.  It requires that underlying transport
   protocols support long-lived, reliable, low-latency, sequenced data
   delivery sessions.  A bi-directional NETCONF session needs to be
   established before any data transfer (or notification) can occur.

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   The XML exchanged within NETCONF messages is structured according to
   YANG modules supported by the NETCONF agent, and the data nodes
   reside within one of possibly many datastores in accordance with the
   Network Management Datastore Architecture (NMDA) of [RFC8342].

   NETCONF transports are required to provide authentication, data
   integrity, confidentiality, and replay protection.  Currently,
   NETCONF can operate over SSH/TCP/IP [RFC6242] or TLS/TCP/IP

5.2.3.  RESTCONF Protocol and Transport

   RESTCONF is a stateless, JSON-encoding-based protocol that provides
   the same operations as NETCONF, using the same YANG modules for
   structure and same NMDA datastores, but using RESTful exchanges over
   HTTP.  It uses HTTP-native methods to express its allowed operations:
   GET, POST, PUT, PATCH, or DELETE data nodes within a datastore.

   Although RESTCONF is a logically stateless protocol, it does rely on
   state within its transport protocol to achieve behaviors such as
   authentication and security sessions.  Because RESTCONF uses the same
   data node semantics of NETCONF, a typical activity can involve the
   use of several sequential round-trips of exchanges to first discover
   managed device state and then act upon it.

5.2.4.  CORECONF Protocol and Transport

   CORECONF is an emerging stateless protocol built atop the Constrained
   Application Protocol (CoAP) [RFC7252] that defines a messaging
   construct developed to operate specifically on constrained devices
   and networks by limiting message size and fragmentation.  CoAP also
   implements a request/response system and methods for GET, POST, PUT,
   and DELETE.

5.3.  gRPC Network Management Interface (gNMI)

   Another emerging but not-IETF-affiliated management protocol is the
   gRPC Network Management Interface (gNMI) [gNMI] which is based on
   gRPC messaging and uses Protobuf data modeling.

   The same limitations of RESTCONF listed above apply to gNMI because
   of its reliance on synchronous HTTP exchanges and TLS security for
   normal operations, as well as the likely deep nesting of data
   schemas.  There is a capability for gNMI to transport JSON-encoded
   YANG-modeled data, but this composing is not fully standardized and
   relies on specific tool integrations to operate.

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5.3.1.  The Protobuf Modeling Language

   The data managed and exchanged via gNMI is encoded and modeled using
   Google Protobuf, an encoding and modeling syntax not affiliated with
   the IETF (although an attempt has been made and abandoned

   Because the Protobuf modeling syntax is relatively low-level (around
   the same as ASN.1 or CBOR), there are some efforts as part of the
   OpenConfig work [gNMI] to translate YANG modules into Protobuf
   schemas (similar to translation to XML or JSON schemas for NETCONF
   and RESTCONF respectively) but there is no required interoperabilty
   between management via gRPC or any of the *CONF protocols.

5.3.2.  gRPC Protocol and Transport

   The message encoding and exchange for gNMI, as the name implies, is
   gRPC protocol [gRPC]. gRPC exclusively uses HTTP/2 [RFC9113] for
   transport and relies on some aspects specific to HTTP/2 for its
   operations (such as HTTP trailer fields).  While not mandated by
   gRPC, when used to transport gNMI data TLS is required for transport

5.4.  Intelligent Platform Management Interface (IPMI)

   A lower-level remote management protocol, intended to be used to
   manage hardware devices and network appliances below the operating
   system (OS), is the Intelligent Platform Management Interface (IPMI)
   standardized in [IPMI].  The IPMI is focused on health monitoring,
   event logging, firmware management, and serial-over-LAN (SOL) remote
   console access in a "pre-OS or OS-absent" host environment.  The IPMI
   operates over a companion Remote Management Control Protocol (RMCP)
   for messaging, which itself can use UDP for transport.

   Because the IPMI and RCMP are tailored to low-level and well-
   connected devices within a datacenter, with typical workflows
   requiring many messaging round trips or low-latency interactive
   sessions, they are not suitable for operation over a challenged

5.5.  Autonomic Networking

   The future of network operations requires more autonomous behavior
   including self-configuration, self-management, self-healing, and
   self-optimization.  One approach to support this is termed Autonomic
   Networking [RFC7575].

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   There is a large and growing set of work within the IETF focused on
   developing an Autonomic Networking Integrated Model and Approach
   (ANIMA).  The ANIMA work has developed a comprehensive reference
   model for distributing autonomic functions across multiple nodes in
   an autonomic networking infrastructure [RFC8993].

   This work, focused on learning the behavior of distributed systems to
   predict future events, is an emerging network management capability.
   This includes the development of signalling protocols such as GRASP
   [RFC8990] and the autonomic control plane (ACP) [RFC8368].

   Both autonomic and challenged networks require similar degrees of
   autonomy.  However, challenged networks cannot provide the complex
   coordination between nodes and distributed supporting infrastructure
   necessary for the frequent data exchanges for negotiation, learning,
   and bootstrapping associated with the above capabilities.

   There is some emerging work in ANIMA as to how disconnected devices
   might join and leave the autonomic control plane over time.  However,
   this work is addressing a different problem than that encountered by
   challenged networks.

5.6.  Deep Space Autonomy

   Outside of the terrestrial networking community, there are existing
   and established remote management systems used for deep space mission
   operations.  Examples of two of these are for the New Horizons
   mission to Pluto [NEW-HORIZONS] and the DART mission to the asteroid
   Dimorphos [DART].

   The DTNMA has some heritage in the concepts of deep space autonomy,
   but each of those mission instantiations use mission-specific data
   encoding, messaging, and transport as well as mission-specific (or
   heavily mission-tailored) modeling concepts and languages.  Part of
   the goal of the DTNMA is to take the proven concepts from these
   missions and standardize a messaging syntax as well as a modular data
   modeling method.

6.  Motivation for New Features

   Management mechanisms that provide the complete set of DTNMA
   desirable properties do not currently exist.  This is not surprising
   since autonomous management in the context of a challenged networking
   environment is a new and emerging use case.

   In particular, a management architecture is needed that integrates
   the following motivating features.

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   Open Loop Control:  Freedom from a request-response architecture,
      API, or other presumption of timely round-trip communications.
      This is particularly important when managing networks that are not
      built over an HTTP or TCP/TLS infrastructure.

   Standard Autonomy Model:  An autonomy model that allows for standard
      expressions of policy to guarantee deterministic behavior across
      devices and vendor implementations.

   Compressible Model Structure:  A data model that allows for very
      compact encodings by defining and exploiting common structures for
      data schemas.

   Combining these new features with existing mechanisms for message
   data exchange (such as BP), data representations (such as CBOR) and
   data modeling languages (such as YANG) will form a pragmatic approach
   to defining challenged network management.

7.  Reference Model

   This section describes a reference model for reasoning about network
   management concepts for challenged networks (generally) and those
   conforming to the DTN architecture (in particular).  The goal of this
   section is to describe how DTNMA services provide DTNMA desirable

7.1.  Important Concepts

   Similar to other network management architectures, the DTNMA draws a
   logical distinction between a managed device and a managing device.
   Managed devices use a DA to manage resident applications.  Managing
   devices use a DM to both monitor and control DAs.

      |  NOTE: The terms "managing" and "managed" represent logical
      |  characteristics of a device and are not, themselves, mutually
      |  exclusive.  For example, a managed device might, itself, also
      |  manage some other device in the network.  Therefore, a device
      |  may support either or both of these characteristics.

   The DTNMA differs from some other management architectures in three
   significant ways, all related to the need for a device to self-manage
   when disconnected from a managing device.

   Pre-shared Definitions:  Managing and managed devices should operate
      using pre-shared data definitions and models.  This implies that
      static definitions should be standardized whenever possible and
      that managing and managed devices may need to negotiate
      definitions during periods of connectivity.

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   Agent Self-Management:  A managed device may find itself disconnected
      from its managing device.  In many challenged networking
      scenarios, a managed device may spend the majority of its time
      without a regular connection to a managing device.  In these
      cases, DAs manage themselves by applying pre-shared policies
      received from managing devices.

   Command-Based Interface:  Managing devices communicate with managed
      devices through a command-based interface.  Instead of exchanging
      variables, objects, or documents, a managing device issues
      commands to be run by a managed device.  These commands may create
      or update variables, change data stores, or impact the managed
      device in ways similar to other network management approaches.
      The use of commands is, in part, driven by the need for DAs to
      receive updates from both remote management devices and local
      autonomy.  The use of controls for the implementation of commands
      is discussed in more detail in Section 9.5.

7.2.  Model Overview

   A DTNMA reference model is provided in Figure 2 below.  In this
   reference model, applications and services on a managing device
   communicate with a DM which uses pre-shared definitions to create a
   set of policy directives that can be sent to a managed device's DA
   via a command-based interface.  The DA provides local monitoring and
   control (commanding) of the applications and services resident on the
   managed device.  The DA also performs local data fusion as necessary
   to synthesize data products (such as reports) that can be sent back
   to the DM when appropriate.

   DTNMA Reference Model

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       Managed Device                            Managing Device
+----------------------------+           +-----------------------------+
| +------------------------+ |           | +-------------------------+ |
| |Applications & Services | |           | | Applications & Services | |
| +----------^-------------+ |           | +-----------^-------------+ |
|            |               |           |             |               |
| +----------v-------------+ |           | +-----------v-------------+ |
| | DTNMA  +-------------+ | |           | | +-----------+   DTNMA   | |
| | AGENT  | Monitor and | | |Commanding | | |  Policy   |  MANAGER  | |
| |        |   Control   | | |<==========| | | Encoding  |           | |
| | +------+-------------+ | |           | | +-----------+-------+   | |
| | |Admin | Data Fusion | | |==========>| | | Reporting | Admin |   | |
| | +------+-------------+ | | Reporting | | +-----------+-------+   | |
| +------------------------+ |           | +-------------------------+ |
+----------------------------+           +-----------------------------+
           ^                                             ^
           |            Pre-Shared Definitions           |
           |        +---------------------------+        |
           +--------| - Autonomy Model          |--------+
                    | - Application Data Models |
                    | - Runtime Data Stores     |

                               Figure 2

   This model preserves the familiar concept of "managers" resident on
   managing devices and "agents" resident on managed devices.  However,
   the DTNMA model is unique in how the DM and DA operate.  The DM is
   used to pre-configure DAs in the network with management policies.
   it is expected that the DAs, themselves, perform monitoring and
   control functions on their own.  In this way, a properly configured
   DA may operate without a reliable connection back to a DM.

7.3.  Functional Elements

   The reference model illustrated in Figure 2 implies the existence of
   certain logical components whose roles and responsibilities are
   discussed in this section.

7.3.1.  Managed Applications and Services

   By definition, managed applications and services reside on a managed
   device.  These software entities can be controlled through some
   interface by the DA and their state can be sampled as part of
   periodic monitoring.  It is presumed that the DA on the managed
   device has the proper data model, control interface, and permissions
   to alter the configuration and behavior of these software

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7.3.2.  DTNMA Agent (DA)

   A DA resides on a managed device.  As is the case with other network
   management approaches, this agent is responsible for the monitoring
   and control of the applications local to that device.  Unlike other
   network management approaches, the agent accomplishes this task
   without a regular connection to a DTNMA Manager.

   The DA performs three major functions on a managed device: the
   monitoring and control of local applications, production of data
   analytics, and the administrative control of the agent itself.  Monitoring and Control

   DAs monitor the status of applications running on their managed
   device and selectively control those applications as a function of
   that monitoring.  The following components are used to perform
   monitoring and control on an agent.

   Rules Database:
           Each DA maintains a database of policy expressions that form
           rules of behavior of the managed device.  Within this
           database, each rule of behavior is a tuple of a stimulus and
           a response.  Within the DTNMA, these rules are the embodiment
           of policy expressions received from DMs and evaluated at
           regular intervals by the autonomy engine.  The rules database
           is the collection of active rules known to the DA.

   Autonomy Engine:
           The DA autonomy engine monitors the state of the managed
           device looking for pre-defined stimuli and, when encountered,
           issuing a pre-defined response.  To the extent that this
           function is driven by the rules database, this engine acts as
           a policy execution engine.  This engine may also be directly
           configured by managers during periods of connectivity for
           actions separate from those in the rules database (such as
           enabling or disabling sets of rules).  Once configured, the
           engine may function without other access to any managing
           device.  This engine may also reconfigure itself as a
           function of policy.

   Application Control Interfaces:
           DAs support control interfaces for all managed applications.
           Control interfaces are used to alter the configuration and
           behavior of an application.  These interfaces may be custom
           for each application, or as provided through a common
           framework such as provided by an operating system.

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   DAs generate new data elements as a function of the current state of
   the managed device and its applications.  These new data products may
   take the form of individual data values, or new collections of data
   used for reporting.  The logical components responsible for these
   behaviors are as follows.

   Application Data Interfaces:
           DAs support mechanisms by which important state is retrieved
           from various applications resident on the managed device.
           These data interfaces may be custom for each application, or
           as provided through a common framework such as provided by an
           operating system.

   Data Value Generators:
           DAs may support the generation of new data values as a
           function of other values collected from the managed device.
           These data generators may be configured with descriptions of
           data values and the data values they generate may be included
           in the overall monitoring and reporting associated with the
           managed device.

   Report Generators:
           DAs may, as appropriate, generate collections of data values
           and provide them to whatever local mechanism takes
           responsibility for their eventual transmission (or expiration
           and removal).  Reports can be generated as a matter of policy
           or in response to the handling of critical events (such as
           errors), or other logging needs.  The generation of a report
           is independent of whether there exists any connectivity
           between a DA and a DM.  Administration

   DAs perform a variety of administrative services in support of their
   configuration, such as the following.

   Manager Mapping:
           The DTNMA allows for a many-to-many relationship amongst
           DTNMA Agents and Managers.  A single DM may configure
           multiple DAs, and a single DA may be configured by multiple
           DMs.  Multiple managers may exist in a network for at least
           two reasons.  First, different managers may exist to control
           different applications on a device.  Second, multiple
           managers increase the likelihood of an agent encountering a
           manager when operating in a sparse or challenged environment.

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           While the need for multiple managers is required for
           operating in a dynamically partitioned network, this
           situation allows for the possibility of conflicting
           information from different managers.  Implementations of the
           DTNMA should consider conflict resolution mechanisms.  Such
           mechanisms might include analyzing managed content, time,
           agent location, or other relevant information to select one
           manager input over other manager inputs.

   Data Verifiers:
           DAs might handle large amounts of data produced by various
           sources, to include data from local managed applications,
           remote managers, and self-calculated values.  DAs should
           ensure, when possible, that externally generated data values
           have the proper syntax and semantic constraints (e.g., data
           type and ranges) and any required authorization.

   Access Controllers:
           DAs support authorized access to the management of individual
           applications, to include the administrative management of the
           agent itself.  This means that a manager may only set policy
           on the agent pursuant to verifying that the manager is
           authorized to do so.

7.3.3.  Managing Applications and Services

   Managing applications and services reside on a managing device and
   serve as the both the source of DA policy statements and the target
   of DA reporting.  They may operate with or without an operator in the

   Unlike management applications in unchallenged networks, these
   applications cannot exert closed-loop control over any managed device
   application.  Instead, they exercise open-loop control by producing
   policies that can be configured and enforced on managed devices by

      |  NOTE: Closed-loop control in this context refers to the
      |  practice of waiting for a response from a managed device prior
      |  to issuing new commands to that device.  These "loops" may be
      |  closed quickly (in milliseconds) or over much longer periods (
      |  hours, days, years).  The alternative to closed-loop control is
      |  open-loop control, where the issuance of new commands is not
      |  dependent on receiving responses to previous commands.
      |  Additionally, there might not be a 1-1 mapping between commands
      |  and responses.  A DA may, for example, produce a single
      |  response that captures the end state from applying multiple
      |  commands.

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7.3.4.  DTNMA Manager (DM)

   A DM resides on a managing device.  This manager provides an
   interface between various managing applications and services and the
   DAs that enforce their policies.  In providing this interface, DMs
   translate between whatever native interface exists to various
   managing applications and the autonomy models used to encode
   management policy.

   The DM performs three major functions on a managing device: policy
   encoding, reporting, and administration.  Policy Encoding

   DMs translate policy directives from managing applications and
   services into standardized policy expressions that can be recognized
   by DAs.  The following logical components are used to perform this
   policy encoding.

   Application Control Interfaces:
           DMs support control interfaces for managing applications.
           These control interfaces are used to receive desired policy
           statements from applications.  These interfaces may be custom
           for each application, or provided through a common framework,
           protocol, or operating system.

   Policy Encoders:
           DAs implement a standardized autonomy model comprising
           standardized data elements.  This allows the open-loop
           control structures provided by managing applications to be
           represented in a common language.  Policy encoders perform
           this encoding function.

   Policy Aggregators:
           DMs collect multiple encoded policies into messages that can
           be sent to DAs over the network.  This implies the proper
           addressing of agents and the creation of messages that
           support store-and-forward operations.  It is recommended that
           control messages be packaged using BP bundles when there may
           be intermittent connectivity between DMs and DAs.  Reporting

   DMs receive reports on the status of managed devices during periods
   of connectivity with the DAs on those devices.  The following logical
   components are needed to implement reporting capabilities on a DM.

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   Report Collectors:
           DMs receive reports from DAs in an asynchronous manner.  This
           means that reports may be received out of chronological order
           and in ways that are difficult or impossible to associate
           with a specific policy from a managing application.  DMs
           collect these reports and extract their data in support of
           subsequent data analytics.

   Data Analyzers:
           DMs review sets of data reports from DAs with the purpose of
           extracting relevant data to communicate with managing
           applications.  This may include simple data extraction or may
           include more complex processing such as data conversion, data
           fusion, and appropriate data analytics.

   Application Data Interfaces:
           DMs support mechanisms by which data retrieved from DAs may
           be provided back to managing devices.  These interfaces may
           be custom for each application, or as provided through a
           common framework, protocol, or operating system.  Administration

   Managers in the DTNMA perform a variety of administrative services,
   such as the following.

   Agent Mappings:
           The DTNMA allows DMs to communicate with multiple DAs.
           However, not every agent in a network is expected to support
           the same set of Application Data Models or otherwise have the
           same set of managed applications running.  For this reason,
           DMs determine individual DA capabilities to ensure that only
           appropriate Controls are sent to a DA.

   Data Verifiers:
           DMs handle large amounts of data produced by various sources,
           to include data from managing applications and DAs.  DMs
           should ensure, when possible, that data values received from
           DAs over a network have the proper syntax and semantic
           constraints (e.g., data type and ranges) and any required

   Access Controllers:
           DMs should only send Controls to agents when the manager is
           configured with appropriate access to both the agent and the
           applications being managed.

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7.3.5.  Pre-Shared Definitions

   A consequence of operating in a challenged environment is the
   potential inability to negotiate information in real-time.  For this
   reason, the DTNMA requires that managed and managing devices operate
   using pre-shared definitions rather than relying on data definition

   The three types of pre-shared definitions in the DTNMA are the DA
   autonomy model, managed application data models, and any runtime data
   shared by managers and agents.

   Autonomy Model:
           A DTNMA autonomy model represents the data elements and
           associated autonomy structures that define the behavior of
           the agent autonomy engine.  A standardized autonomy model
           allows for individual implementations of DAs, and DMs to
           interoperate.  A standardized model also provides guidance to
           the design and implementation of both managed and managing

   Application Data Models:
           As with other network management architectures, the DTNMA
           pre-supposes that managed applications (and services) define
           their own data models.  These data models include the data
           produced by, and Controls implemented by, the application.
           These models are expected to be static for individual
           applications and standardized for applications implementing
           standard protocols.

   Runtime Data Stores:
           Runtime data stores, by definition, include data that is
           defined at runtime.  As such, the data is not pre-shared
           prior to the deployment of DMs and DAs.  Pre-sharing in this
           context means that DMs and DAs are able to define and
           synchronize data elements prior to their operational use in
           the system.  This synchronization happens during periods of
           connectivity between DMs and DAs.

8.  Desired Services

   This section describes the services provided by DTNMA components on
   both managing and managed devices.  Many of the services discussed in
   this section attempt to provide continuous operation of a managed
   device through periods of no connectivity with a managing device.

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8.1.  Local Monitoring and Control

   DTNMA monitoring is associated with some DA autonomy engine.  The
   term monitoring implies regular access to information such that state
   changes may be acted upon within some response time period.

   Predicate autonomy on a managed device should collect state
   associated with the device at regular intervals and evaluate that
   collected state for any changes that require a preventative or
   corrective action.  Similarly, this monitoring may cause the device
   to generate one or more reports destined to a managing device.

   Similar to monitoring, DTNMA control results in actions by the agent
   to change the state or behavior of the managed device.  All control
   in the DTNMA is local control.  In cases where there exists a timely
   connection to a manager, received Controls are still evaluated and
   run locally as part of local autonomy.  In this case, the autonomy
   stimulus is the receipt of the Control and the response is to
   immediately run the Control.  In this way, there is never a
   dependency on a session or other stateful exchange with any remote

8.2.  Local Data Fusion

   DTNMA Fusion services produce new data products from existing state
   on the managed device.  These fusion products can be anything from
   simple summations of sampled counters to complex calculations of
   behavior over time.

   Fusion is an important service in the DTNMA because fusion products
   are part of the overall state of a managed device.  Complete
   knowledge of this overall state is important for the management of
   the device and the predicates of rules on a DA may refer to fused

   In-situ data fusion is an important function as it allows for the
   construction of intermediate summary data, the reduction of stored
   and transmitted raw data, possibly fewer predicates in rule
   definitions, and otherwise insulates the data source from conclusions
   drawn from that data.

   The DTNMA requires fusion to occur on the managed device itself.  If
   the network is partitioned such that no connection to a managing
   device is available, then fusion needs to happen locally.  Similarly,
   connections to a managing device might not remain active long enough
   for round-trip data exchange or may not have the bandwidth to send
   all sampled data.

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      |  NOTE: The DTNMA does not restrict the storage and transmission
      |  of raw (pre-fused) data.  Such raw data can be useful for
      |  debugging managed devices, understanding complex interactions
      |  and underlying conditions, and tuning for better performance
      |  and/or better outcomes.

8.3.  Remote Configuration

   DTNMA configuration services update the local configuration of a
   managed device with the intent to impact the behavior and
   capabilities of that device.

   The DTNMA configuration service is unique in that the selection of
   managed device configurations occurs as a function of the state of
   the device.  This implies that management proxies on the device store
   multiple configuration functions that can be applied as needed
   without consultation from a managing device.

      |  This approach differs from other management concepts of
      |  selecting from multiple datastores.  DTNMA configuration
      |  functions can target individual data elements and can calculate
      |  new values from local device state.

   When detecting stimuli, the agent autonomy engine supports a
   mechanism for evaluating whether application monitoring data or
   runtime data values are recent enough to indicate a change of state.
   In cases where data has not been updated recently, it may be
   considered stale and not used to reliably indicate that some stimulus
   has occurred.

8.4.  Remote Reporting

   DTNMA reporting services collect information known to the managed
   device and prepare it for eventual transmission to one or more
   managing devices.  The contents of these reports, and the frequency
   at which they are generated, occurs as a function of the state of the
   managed device, independent of the managing device.

   Once generated, it is expected that reports might be queued pending a
   connection back to a managing device.  Therefore, reports need to be
   differentiable as a function of the time they were generated.

      |  NOTE: When reports are queued pending transmission, the overall
      |  storage capacity at the queuing device needs to be considered.
      |  There may be cases where queued reports can be considered
      |  expired either because they have been queued for too long, or
      |  because they have been replaced by a newer report.  When a
      |  report is considered expired, it may be considered for removal

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      |  and, thus, never transmitted.  This consideration is expected
      |  to be part of the implementation of the queuing device and not
      |  the responsibility of the reporting function within the DTNMA.

   When reports are sent to a managing device over a challenged network,
   they may arrive out of order due to taking different paths through
   the network or being delayed due to retransmissions.  A managing
   device should not infer meaning from the order in which reports are

   Reports may or may not be associated with a specific Control.  Some
   reports may be annotated with the Control that caused the report to
   be generated.  Sometimes, a single report will represent the end
   state of applying multiple Controls.

8.5.  Authorization

   Both local and remote services provided by the DTNMA affect the
   behavior of multiple applications on a managed device and may
   interface with multiple managing devices.

   Authorization services enforce the potentially complex mapping of
   other DTNMA services amongst managed and managing devices in the
   network.  For example, fine-grained access control can determine
   which managing devices receive which reports, and what Controls can
   be used to alter which managed applications.

   This is particularly beneficial in networks that either deal with
   multiple administrative entities or overlay networks that cross
   administrative boundaries.  Allowlists, blocklists, key-based
   infrastructures, or other schemes may be used for this purpose.

9.  Logical Autonomy Model

   An important characteristic of the DTNMA is the shift in the role of
   a managing device.  One way to describe the behavior of the agent
   autonomy engine is to describe the characteristics of the autonomy
   model it implements.

   This section describes a logical autonomy model in terms of the
   abstract data elements that would comprise the model.  Defining
   abstract data elements allows for an unambiguous discussion of the
   behavior of an autonomy model without mandating a particular design,
   encoding, or transport associated with that model.

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9.1.  Overview

   A managing autonomy capability on a potentially disconnected device
   needs to behave in both an expressive and deterministic way.
   Expressivity allows for the model to be configured for a wide range
   of future situations.  Determinism allows for the forensic
   reconstruction of device behavior as part of debugging or recovery
   efforts.  It also is necessary to ensure predictable behavior.

      |  NOTE: The use of predicate logic and a stimulus-response system
      |  does not conflict with the use of higher-level autonomous
      |  function or the incorporation of machine learning.
      |  Specifically, the DTNMA deterministic autonomy model can
      |  coexist with other autonomous functions managing applications
      |  and network services.
      |  An example of such co-existence is the use of the DTNMA model
      |  to ensure a device stays within safe operating parameters while
      |  a less deterministic machine learning model directs smaller
      |  behaviors for the device.

   The DTNMA autonomy model is a rule-based model in which individual
   rules associate a pre-identified stimulus with a pre-configured
   response to that stimulus.

   Stimuli are identified using one or more predicate logic expressions
   that examine aspects of the state of the managed device.  Responses
   are implemented by running one or more procedures on the managed

   In its simplest form, a stimulus is a single predicate expression of
   a condition that examines some aspect of the state of the managed
   device.  When the condition is met, a predetermined response is
   applied.  This behavior can be captured using the construct:

               IF <condition 1> THEN <response 1>;

   In more complex forms, a stimulus may include both a common condition
   shared by multiple rules and a specific condition for each individual
   rule.  If the common condition is not met, the evaluation of the
   specific condition of each rule sharing the common condition can be
   skipped.  In this way, the total number of predicate evaluations can
   be reduced.  This behavior can be captured using the construct:

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               IF <common condition> THEN
                 IF <specific condition 1> THEN <response 1>
                 IF <specific condition 2> THEN <response 2>
                 IF <specific condition 3> THEN <response 3>

      |  NOTE: The DTNMA model remains a stimulus-response system,
      |  regardless of whether a common condition is part of the
      |  stimulus.  However, it is recommended that implementations
      |  incorporate a common condition because of the efficiency
      |  provided by such a bulk evaluation.
      |  NOTE: One use of a stimulus "common condition" is to associated
      |  the condition with an on-board event such as the expiring of a
      |  timer or the changing of a monitored value.
      |  NOTE: The DTNMA does not prescribe when to evaluate rule
      |  stimuli.  Implementations may choose to evaluate rule stimuli
      |  at periodic intervals (such as 1Hz or 100Hz).  When stimuli
      |  include on-board events, implementations may choose to perform
      |  an immediate evaluation at the time of the event rather than
      |  waiting for a periodic evaluation.

   DTNMA Autonomy Model

  Managed Applications |           DTNMA Agent          | DTNMA Manager
                       |   +---------+                  |
                       |   |  Local  |                  |   Encoded
                       |   | Rule DB |<-------------------- Policy
                       |   +---------+                  |   Expressions
                       |        ^                       |
                       |        |                       |
                       |        v                       |
                       |   +----------+    +---------+  |
     Monitoring Data------>|   Agent  |    | Runtime |  |
                       |   | Autonomy |<-->|  Data   |<---- Definitions
 Application Control<------|  Engine  |    |  Store  |  |
                       |   +----------+    +---------+  |
                       |         |                      |
                       |         +-------------------------> Reports
                       |                                |

                                Figure 3

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   The flow of data into and out of the agent autonomy engine is
   illustrated in Figure 3.  In this model, the autonomy engine stores
   the combination of stimulus conditions and associated responses as a
   set of "rules" in a rules database.  This database is updated through
   the execution of the autonomy engine and as configured from policy
   statements received by managers.

   Stimuli are detected by examining the state of applications as
   reported through application monitoring interfaces and through any
   locally-derived data.  Local data is calculated in accordance with
   definitions also provided by managers as part of the runtime data

   Responses to stimuli may include updates to the rules database,
   updates to the runtime data store, Controls sent to applications, and
   the generation of reports.

9.2.  Model Characteristics

   There are several practical challenges to the implementation of a
   distributed rule-based system.  Large numbers of rules may be
   difficult to understand, deconflict, and debug.  Rules whose
   conditions are given by fused or other dynamic data may require data
   logging and reporting for deterministic offline analysis.  Rule
   differences across managed devices may lead to oscillating effects.
   This section identifies those characteristics of an autonomy model
   that might help implementations mitigate some of these challenges.

   There are a number of ways to represent data values, and many data
   modeling languages exist for this purpose.  When considering how to
   model data in the context of the DTNMA autonomy model there are some
   modeling features that should be present to enable functionality.
   There are also some modeling features that should be prevented to
   avoid ambiguity.

   Traditional network management approaches favor flexibility in their
   data models.  The DTNMA stresses deterministic behavior that supports
   forensic analysis of agent activities "after the fact".  As such, the
   following statements should be true of all data representations
   relating to DTNMA autonomy.

   Strong Typing:  The predicates and expressions that comprise the
      autonomy services in the DTNMA should require strict data typing.
      This avoids errors associated with implicit data conversions and
      helps detect misconfiguration.

   Acyclic Dependency:  Many dependencies exist in an autonomy model,

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      particularly when combining individual expressions or results to
      create complex behaviors.  Implementations that conform to the
      DTNMA need to prevent circular dependencies.

   Fresh Data:  Autonomy models operating on data values presume that
      their data inputs represent the actionable state of the managed
      device.  If a data value has failed to be refreshed within a time
      period, autonomy might incorrectly infer an operational state.
      Regardless of whether a data value has changed, DTNMA
      implementations should provide some indicator of whether the data
      value is "fresh" meaning that it still represents the current
      state of the device.

   Pervasive Parameterization:  Where possible, autonomy model objects
      should support parameterization to allow for flexibility in the
      specification.  Parameterization allows for the definition of
      fewer unique model objects and also can support the substitution
      of local device state when exercising device control or data

   Configurable Cardinality:  The number of data values that can be
      supported in a given implementation is finite.  For devices
      operating in challenged environments, the number of supported
      objects may be far fewer than that which can be supported by
      devices in well-resourced environments.  DTNMA implementations
      should define limits to the number of supported objects that can
      be active in a system at one time, as a function of the resources
      available to the implementation.

   Control-Based Updates:  The agent autonomy engine changes the state
      of the managed device by running Controls on the device.  This is
      different from approaches where the behavior of a managed device
      is influenced by updating configuration values, such as in a table
      or datastore.  Altering behavior via one or more Controls allows
      checking all pre-conditions before making changes as well as
      providing more granularity in the way in which the device is
      updated.  Where necessary, Controls can be defined to perform bulk
      updates of configuration data so as not to lose that update
      modality.  One important update pre-condition is that the system
      is not performing an action that would prevent the update (such as
      currently applying a competing update).

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9.3.  Data Value Representation

   The expressive representation of simple data values is fundamental to
   the successful construction and evaluation of predicates in the DTNMA
   autonomy model.  When defining such values, there are useful
   distinctions regarding how values are identified and whether values
   are generated internal or external to the autonomy model.

   A DTNMA data value should combine a base type (e.g., integer, real,
   string) representation with relevant semantic information.  Base
   types are used for proper storage and encoding.  Semantic information
   allows for additional typing, constraint definitions, and mnemonic
   naming.  This expanded definition of data value allows for better
   predicate construction and evaluation and early type checking.

   Data values may further be annotated based on whether their value is
   the result of a DA calculation or the result of some external process
   on the managed device.  For example, operators may with to know which
   values can be updated by actions on the DA versus which values (such
   as sensor readings) cannot be reliably changed because they are
   calculated external to the DA.

9.4.  Data Reporting

   The DTNMA autonomy model should, as required, report on the state of
   its managed device (to include the state of the model itself).  This
   reporting should be done as a function of the changing state of the
   managed device, independent of the connection to any managing device.
   Queuing reports allows for later forensic analysis of device
   behavior, which is a desirable property of DTNMA management.

   DTNMA data reporting consists of the production of some data report
   instance conforming to a data report schema.  The use of schemas
   allows a report instance to identify the schema to which it conforms
   instead of carrying the structure in the report itself.  This
   approach can significantly reduce the size of generated reports.

      |  NOTE: The DTNMA data reporting concept is intentionally
      |  distinct from the concept of exchanging data stores across a
      |  network.  It is envisioned that a DA might generate a data
      |  report instance of a data report schema at regular intervals or
      |  in response to local events.  In this model, many report
      |  schemas may be defined to capture unique, relevant combinations
      |  of known data values rather than sending bulk data stores off-
      |  platform for analysis.

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      |  NOTE: It is not required that data report schemas be tabular in
      |  nature.  Individual implementations might define tabular
      |  schemas for table-like data and other report schemas for more
      |  heterogeneous reporting.

9.5.  Command Execution

   The agent autonomy engine requires that managed devices issue
   commands on themselves as if they were otherwise being controlled by
   a managing device.  The DTNMA implements commanding through the use
   of Controls and macros.

   Controls represent parameterized, predefined procedures run by the DA
   either as directed by the DM or as part of a rule response from the
   DA autonomy engine.  Macros represent ordered sequences of Controls.

   Controls are conceptually similar to RPCs in that they represent
   parameterized functions run on the managed device.  However, they are
   conceptually dissimilar from RPCs in that they do not have a concept
   of a return code because they operate over an asynchronous transport.
   The concept of return code in an RPC implies a synchronous
   relationship between the caller of the procedure and the procedure
   being called, which might not be possible within the DTNMA.

   The success or failure of a Control may be handled locally by the
   agent autonomy engine.  Local error handling is particularly
   important in this architecture given the potential for long periods
   of disconnectivity between a DA and a DM.  The failure of one or more
   Controls is part of the state of the DA and can be used to trigger
   rules within the DA autonomy engine.

   The impact of a Control is externally observable via the generation
   and eventual examination of data reports produced by the managed

   The failure of certain Controls might leave a managed device in an
   undesired state.  Therefore, it is important that there be
   consideration for Control-specific recovery mechanisms (such as a
   rollback or safing mechanism).  When a Control that is part of a
   macro (such as in an autonomy response) fails, there may be a need to
   implement a safe state for the managed device based on the nature of
   the failure.

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      |  NOTE: The use of the term Control in the DTNMA is derived in
      |  part from the concept of Command and Control (C2) where control
      |  implies the operational instructions undertaken to implement
      |  (or maintain) a commanded objective.  The DA autonomy engine
      |  implements controls on a managed device to allow it to fulfill
      |  some commanded objective known by a (possibly disconnected)
      |  managing device.
      |  For example, a device might be commanded to maintain a safe
      |  internal thermal environment.  Actions taken by a DA to manage
      |  heaters, louvers, and other temperature-effecting components
      |  are controls taken in service of that commanded objective.

9.6.  Predicate Autonomy Rules

   As discussed in Section 9.1, the DTNMA rule-based stimulus-response
   system associates stimulus detection with a predetermined response.
   Rules may be categorized based on whether their stimuli include
   generic statements of managed device state or whether they are
   optimized to only consider the passage of time on the device.

   State-based rules are those whose stimulus is based on the evaluated
   state of the managed device.  Time-based rules are a unique subset of
   state-based rules whose stimulus is given only by a time-based event.
   Implementations might create different structures and evaluation
   mechanisms for these two different types of rules to achieve more
   efficient processing on a platform.

10.  Use Cases

   Using the autonomy model defined in Section 9, this section describes
   flows through sample configurations conforming to the DTNMA.  These
   use cases illustrate remote configuration, local monitoring and
   control, multiple manager support, and data fusion.

10.1.  Notation

   The use cases presented in this section are documented with a
   shorthand notation to describe the types of data sent between
   managers and agents.  This notation, outlined in Table 1, leverages
   the definitions of autonomy model components defined in Section 9.

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   |       Term       |             Definition            |  Example  |
   |       EDD#       |  Externally Defined Data - a data |   EDD1,   |
   |                  | value defined external to the DA. |    EDD2   |
   |        V#        |  Variable - a data value defined  | V1 = EDD1 |
   |                  |        internal to the DA.        |    + 7    |
   |       EXPR       |   Predicate expression - used to  |   V1 > 5  |
   |                  |      define a rule stimulus.      |           |
   |        ID        |      DTNMA Object Identifier.     |  V1, EDD2 |
   |       ACL#       |  Enumerated Access Control List.  |    ACL1   |
   | DEF(ACL,ID,EXPR) | Define ID from expression.  Allow | DEF(ACL1, |
   |                  |  managers in ACL to see this ID.  |  V1, EDD1 |
   |                  |                                   |  + EDD2)  |
   |    PROD(P,ID)    | Produce ID according to predicate |  PROD(1s, |
   |                  |  P.  P may be a time period (1s)  |   EDD1)   |
   |                  |   or an expression (EDD1 > 10).   |           |
   |     RPT(ID)      | A report instance containing data | RPT(EDD1) |
   |                  |             named ID.             |           |

                           Table 1: Terminology

   These notations do not imply any implementation approach.  They only
   provide a succinct syntax for expressing the data flows in the use
   case diagrams in the remainder of this section.

10.2.  Serialized Management

   This nominal configuration shows a single DM interacting with
   multiple DAs.  The control flows for this scenario are outlined in
   Figure 4.

   Serialized Management Control Flow

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         +-----------+           +---------+           +---------+
         |   DTNMA   |           |  DTNMA  |           |  DTNMA  |
         | Manager A |           | Agent A |           | Agent B |
         +----+------+           +----+----+           +----+----+
             |                       |                     |
             |-----PROD(1s, EDD1)--->|                     | (1)
             |----------------------------PROD(1s, EDD1)-->|
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     | (2)
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |                       |                     |

                                  Figure 4

   In a serialized management scenario, a single DM interacts with
   multiple DAs.

   In this figure, the DTNMA Manager A sends a policy to DTNMA Agents A
   and B to report the value of an EDD (EDD1) every second in (step 1).
   Each DA receives this policy and configures their respective autonomy
   engines for this production.  Thereafter, (step 2) each DA produces a
   report containing data element EDD1 and sends those reports back to
   the DM.

   This behavior continues without any additional communications from
   the DM.

10.3.  Intermittent Connectivity

   Building from the nominal configuration in Section 10.2, this
   scenario shows a challenged network in which connectivity between
   DTNMA Agent B and the DM is temporarily lost.  Control flows for this
   case are outlined in Figure 5.

   Challenged Management Control Flow

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         +-----------+           +---------+           +---------+
         |   DTNMA   |           |  DTNMA  |           |  DTNMA  |
         | Manager A |           | Agent A |           | Agent B |
         +----+------+           +----+----+           +----+----+
             |                       |                     |
             |-----PROD(1s, EDD1)--->|                     | (1)
             |----------------------------PROD(1s, EDD1)-->|
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     | (2)
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |                       |            RPT(EDD1)| (3)
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |                       |            RPT(EDD1)| (4)
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |<----------------RPT(EDD1), RPT(EDD1)--------| (5)
             |                       |                     |

                                  Figure 5

   In a challenged network, DAs store reports pending a transmit

   In this figure, DTNMA Manager A sends a policy to DTNMA Agents A and
   B to produce an EDD (EDD1) every second in (step 1).  Each DA
   receives this policy and configures their respective autonomy engines
   for this production.  Produced reports are transmitted when there is
   connectivity between the DA and DM (step 2).

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   At some point, DTNMA Agent B loses the ability to transmit in the
   network (steps 3 and 4).  During this time period, DA B continues to
   produce reports, but they are queued for transmission.  This queuing
   might be done by the DA itself or by a supporting transport such as
   BP.  Eventually (and before the next scheduled production of EDD1),
   DTNMA Agent B is able to transmit in the network again (step 5) and
   all queued reports are sent at that time.  DTNMA Agent A maintains
   connectivity with the DM during steps 3-5, and continues to send
   reports as they are generated.

10.4.  Open-Loop Reporting

   This scenario illustrates the DTNMA open-loop control paradigm, where
   DAs manage themselves in accordance with policies provided by DMs,
   and provide reports to DMs based on these policies.

   The control flow shown in Figure 6, includes an example of data
   fusion, where multiple policies configured by a DM result in a single
   report from a DA.

   Consolidated Management Control Flow

         +-----------+           +---------+           +---------+
         |   DTNMA   |           |  DTNMA  |           |  DTNMA  |
         | Manager A |           | Agent A |           | Agent B |
         +----+------+           +----+----+           +----+----+
             |                       |                     |
             |-----PROD(1s, EDD1)--->|                     | (1)
             |----------------------------PROD(1s, EDD1)-->|
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     | (2)
             |                       |                     |
             |                       |                     |
             |----------------------------PROD(1s, EDD2)-->| (3)
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |<--------------------------RPT(EDD1,EDD2)----| (4)
             |                       |                     |
             |                       |                     |
             |<-------RPT(EDD1)------|                     |
             |                       |                     |

                                  Figure 6

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   A many-to-one mapping between management policy and device state
   reporting is supported by the DTNMA.

   In this figure, DTNMA Manager A sends a policy statement in the form
   of a rule to DTNMA Agents A and B, which instructs the DAs to produce
   a report with EDD1 every second (step 1).  Each DA receives this
   policy, which is stored in its respective Rule Database, and
   configures its Autonomy Engine.  Reports are transmitted by each DA
   when produced (step 2).

   At a later time, DTNMA Manager A sends an additional policy to DTNMA
   Agent B, requesting the production of a report for EDD2 every second
   (step 3).  This policy is added to DTNMA Agent B's Rule Database.

   Following this policy update, DTNMA Agent A will continue to produce
   EDD1 and DTNMA Agent B will produce both EDD1 and EDD2 (step 4).
   However, DTNMA Agent B may provide these values to the DM in a single
   report rather than as 2 independent reports.  In this way, there is
   no direct mapping between the single consolidated report sent by
   DTNMA Agent B (step 4) and the two different policies sent to DTNMA
   Agent B that caused that report to be generated (steps 1 and 3).

10.5.  Multiple Administrative Domains

   The managed applications on a DA may be controlled by different
   administrative entities in a network.  The DTNMA allows DAs to
   communicate with multiple DMs in the network, such as in cases where
   there is one DM per administrative domain.

   Whenever a DM sends a policy expression to a DA, that policy
   expression may be associated with authorization information.  One
   method of representing this is an ACL.

      |  The use of an ACL in this use case does not imply the DTNMA
      |  requires ACLs to annotate policy expressions.  ACLs and their
      |  representation in this context are for example purposes only.

   The ability of one DM to access the results of policy expressions
   configured by some other DM will be limited to the authorization
   annotations of those policy expressions.

   An example of multi-manager authorization is illustrated in Figure 7.

   Multiplexed Management Control Flow

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   +-----------+               +---------+                 +-----------+
   |   DTNMA   |               |  DTNMA  |                 |   DTNMA   |
   | Manager A |               | Agent A |                 | Manager B |
   +-----+-----+               +----+----+                 +-----+-----+
        |                          |                            |
        |---DEF(ACL1,V1,EDD1*2)--->|<---DEF(ACL2, V2, EDD2*2)---| (1)
        |                          |                            |
        |---PROD(1s, V1)---------->|<---PROD(1s, V2)------------| (2)
        |                          |                            |
        |<--------RPT(V1)----------|                            | (3)
        |                          |--------RPT(V2)------------>|
        |<--------RPT(V1)----------|                            |
        |                          |--------RPT(V2)------------>|
        |                          |                            |
        |                          |<---PROD(1s, V1)------------| (4)
        |                          |                            |
        |                          |----ERR(V1 no perm.)------->|
        |                          |                            |
        |--DEF(NULL,V3,EDD3*3)---->|                            | (5)
        |                          |                            |
        |---PROD(1s, V3)---------->|                            | (6)
        |                          |                            |
        |                          |<----PROD(1s, V3)-----------|
        |                          |                            |
        |<--------RPT(V3)----------|--------RPT(V3)------------>| (7)
        |<--------RPT(V1)----------|                            |
        |                          |--------RPT(V2)------------>|
        |<-------RPT(V1)-----------|                            |
        |                          |--------RPT(V2)------------>|

                                  Figure 7

   Multiple DMs may interface with a single DA, particularly in complex

   In this figure, both DTNMA Managers A and B send policies to DTNMA
   Agent A (step 1).  DM A defines a variable (V1) whose value is given
   by the mathematical expression (EDD1 * 2) and is associated with an
   ACL (ACL1) that restricts access to V1 to DM A only.  Similarly, DM B
   defines a variable (V2) whose value is given by the mathematical
   expression (EDD2 * 2) and associated with an ACL (ACL2) that
   restricts access to V2 to DM B only.

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   Both DTNMA Managers A and B also send policies to DTNMA Agent A to
   report on the values of their variables at 1 second intervals (step
   2).  Since DM A can access V1 and DM B can access V2, there is no
   authorization issue with these policies and they are both accepted by
   the autonomy engine on Agent A.  Agent A produces reports as
   expected, sending them to their respective managers (step 3).

   Later (step 4) DM B attempts to configure DA A to also report to it
   the value of V1.  Since DM B does not have authorization to view this
   variable, DA A does not include this in the configuration of its
   autonomy engine and, instead, some indication of permission error is
   included in any regular reporting back to DM B.

   DM A also sends a policy to Agent A (step 5) that defines a variable
   (V3) whose value is given by the mathematical expression (EDD3 * 3)
   and is not associated with an ACL, indicating that any DM can access
   V3.  In this instance, both DM A and DM B can then send policies to
   DA A to report the value of V3 (step 6).  Since there is no
   authorization restriction on V3, these policies are accepted by the
   autonomy engine on Agent A and reports are sent to both DM A and B
   over time (step 7).

10.6.  Cascading Management

   There are times where a single network device may serve as both a DM
   for other DAs in the network and, itself, as a device managed by
   someone else.  This may be the case on nodes serving as gateways or
   proxies.  The DTNMA accommodates this case by allowing a single
   device to run both a DA and DM.

   An example of this configuration is illustrated in Figure 8.

   Cascading Management Control Flow

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                  |                Node B               |
                  |                                     |
   +-----------+  |   +-----------+       +---------+   |    +---------+
   |   DTNMA   |  |   |   DTNMA   |       |  DTNMA  |   |    |  DTNMA  |
   | Manager A |  |   | Manager B |       | Agent B |   |    | Agent C |
   +---+-------+  |   +-----+-----+       +----+----+   |    +----+----+
       |          |         |                  |        |         |
       |--------------DEF(NULL,V0,EDD1+EDD2)-->|        |         | (1)
       |--------------PROD(1s,V0)------------->|        |         |
       |          |         |                  |        |         |
       |          |         |--PROD(1s,EDD1)-->|        |         | (2)
       |          |         |---------------------PROD(1s,EDD2)-->| (2)
       |          |         |                  |        |         |
       |          |         |                  |        |         |
       |          |         |<----RPT(EDD1)----|        |         | (3)
       |          |         |<--------------------RPT(EDD2)-------| (3)
       |          |         |                  |        |         |
       |<-------------RPT(V0)------------------|        |         | (4)
       |          |         |                  |        |         |
       |          |         |                  |        |         |
                  |                                     |
                  |                                     |

                                  Figure 8

   A device can operate as both a DTNMA Manager and an Agent.

   In this example, we presume that DA B is able to sample a given EDD
   (EDD1) and that DA C is able to sample a different EDD (EDD2).  Node
   B houses DM B (which controls DA C) and DA B (which is controlled by
   DM A).  DM A must periodically receive some new value that is
   calculated as a function of both EDD1 and EDD2.

   First, DM A sends a policy to DA B to define a variable (V0) whose
   value is given by the mathematical expression (EDD1 + EDD2) without a
   restricting ACL.  Further, DM A sends a policy to DA B to report on
   the value of V0 every second (step 1).

   DA B needs the ability to monitor both EDD1 and EDD2.  However, the
   only way to receive EDD2 values is to have them reported back to Node
   B by DA C and included in the Node B runtime data stores.  Therefore,
   DM B sends a policy to DA C to report on the value of EDD2 (step 2).

   DA C receives the policy in its autonomy engine and produces reports
   on the value of EDD2 every second (step 3).

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   DA B may locally sample EDD1 and EDD2 and uses that to compute values
   of V0 and report on those values at regular intervals to DM A (step

   While a trivial example, the mechanism of associating fusion with the
   Agent function rather than the Manager function scales with fusion
   complexity.  Within the DTNMA, DAs and DMs are not required to be
   separate software implementations.  There may be a single software
   application running on Node B implementing both DM B and DA B roles.

11.  IANA Considerations

   This document requires no IANA actions.

12.  Security Considerations

   Security within a DTNMA exists in at least two layers: security in
   the data model and security in the messaging and encoding of the data

   Data model security refers to the validity and accessibility of data
   elements.  For example, a data element might be available to certain
   DAs or DMs in a system, whereas the same data element may be hidden
   from other DAs or DMs.  Both verification and authorization
   mechanisms at DAs and DMs are important to achieve this type of

      |  NOTE: One way to provide finer-grained application security is
      |  through the use of Access Control Lists (ACLs) that would be
      |  defined as part of the configuration of DAs and DMs.  It is
      |  expected that many common data model tools provide mechanisms
      |  for the definition of ACLs and best practices for their
      |  operational use.

   The exchange of information between and amongst DAs and DMs in the
   DTNMA is expected to be accomplished through some secured messaging

13.  Informative References

   [ASN.1]    International Organization for Standardization,
              "Information processing systems - Open Systems
              Interconnection - Specification of Abstract Syntax
              Notation One (ASN.1)", International Standard 8824,
              December 1987.

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   [DART]     Tropf, B. T., Haque, M., Behrooz, N., and C. Krupiarz,
              "The DART Autonomy System", 2023,

   [gNMI]     OpenConfig, "gRPC Network Management Interface (gNMI)",
              May 2023, <

   [gRPC]     gRPC Authors, "gRPC Documentation", 2024,

              Veillette, M., Van der Stok, P., Pelov, A., Bierman, A.,
              and C. Bormann, "CoAP Management Interface (CORECONF)",
              Work in Progress, Internet-Draft, draft-ietf-core-comi-17,
              4 March 2024, <

              Veillette, M., Pelov, A., Petrov, I., Bormann, C., and M.
              Richardson, "YANG Schema Item iDentifier (YANG SID)", Work
              in Progress, Internet-Draft, draft-ietf-core-sid-24, 22
              December 2023, <

              Stuart, S. and R. Fernando, "Encoding rules and MIME type
              for Protocol Buffers", Work in Progress, Internet-Draft,
              draft-rfernando-protocol-buffers-00, 11 October 2012,

   [IPMI]     Intel, Hewlett-Packard, NEC, and Dell, "Intelligent
              Platform Management Interface Specification, Second
              Generation", October 2013,

              Moore, R. C., "Autonomous safeing and fault protection for
              the New Horizons mission to Pluto", March 2007,

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   [RFC2578]  McCloghrie, K., Ed., Perkins, D., Ed., and J.
              Schoenwaelder, Ed., "Structure of Management Information
              Version 2 (SMIv2)", STD 58, RFC 2578,
              DOI 10.17487/RFC2578, April 1999,

   [RFC2982]  Kavasseri, R., Ed., "Distributed Management Expression
              MIB", RFC 2982, DOI 10.17487/RFC2982, October 2000,

   [RFC3165]  Levi, D. and J. Schoenwaelder, "Definitions of Managed
              Objects for the Delegation of Management Scripts",
              RFC 3165, DOI 10.17487/RFC3165, August 2001,

   [RFC3410]  Case, J., Mundy, R., Partain, D., and B. Stewart,
              "Introduction and Applicability Statements for Internet-
              Standard Management Framework", RFC 3410,
              DOI 10.17487/RFC3410, December 2002,

   [RFC3411]  Harrington, D., Presuhn, R., and B. Wijnen, "An
              Architecture for Describing Simple Network Management
              Protocol (SNMP) Management Frameworks", STD 62, RFC 3411,
              DOI 10.17487/RFC3411, December 2002,

   [RFC3414]  Blumenthal, U. and B. Wijnen, "User-based Security Model
              (USM) for version 3 of the Simple Network Management
              Protocol (SNMPv3)", STD 62, RFC 3414,
              DOI 10.17487/RFC3414, December 2002,

   [RFC3416]  Presuhn, R., Ed., "Version 2 of the Protocol Operations
              for the Simple Network Management Protocol (SNMP)",
              STD 62, RFC 3416, DOI 10.17487/RFC3416, December 2002,

   [RFC3417]  Presuhn, R., Ed., "Transport Mappings for the Simple
              Network Management Protocol (SNMP)", STD 62, RFC 3417,
              DOI 10.17487/RFC3417, December 2002,

   [RFC3418]  Presuhn, R., Ed., "Management Information Base (MIB) for
              the Simple Network Management Protocol (SNMP)", STD 62,
              RFC 3418, DOI 10.17487/RFC3418, December 2002,

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   [RFC4838]  Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst,
              R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant
              Networking Architecture", RFC 4838, DOI 10.17487/RFC4838,
              April 2007, <>.

   [RFC4949]  Shirey, R., "Internet Security Glossary, Version 2",
              FYI 36, RFC 4949, DOI 10.17487/RFC4949, August 2007,

   [RFC5591]  Harrington, D. and W. Hardaker, "Transport Security Model
              for the Simple Network Management Protocol (SNMP)",
              STD 78, RFC 5591, DOI 10.17487/RFC5591, June 2009,

   [RFC5592]  Harrington, D., Salowey, J., and W. Hardaker, "Secure
              Shell Transport Model for the Simple Network Management
              Protocol (SNMP)", RFC 5592, DOI 10.17487/RFC5592, June
              2009, <>.

   [RFC5652]  Housley, R., "Cryptographic Message Syntax (CMS)", STD 70,
              RFC 5652, DOI 10.17487/RFC5652, September 2009,

   [RFC6241]  Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
              and A. Bierman, Ed., "Network Configuration Protocol
              (NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,

   [RFC6242]  Wasserman, M., "Using the NETCONF Protocol over Secure
              Shell (SSH)", RFC 6242, DOI 10.17487/RFC6242, June 2011,

   [RFC6353]  Hardaker, W., "Transport Layer Security (TLS) Transport
              Model for the Simple Network Management Protocol (SNMP)",
              STD 78, RFC 6353, DOI 10.17487/RFC6353, July 2011,

   [RFC6991]  Schoenwaelder, J., Ed., "Common YANG Data Types",
              RFC 6991, DOI 10.17487/RFC6991, July 2013,

   [RFC7228]  Bormann, C., Ersue, M., and A. Keranen, "Terminology for
              Constrained-Node Networks", RFC 7228,
              DOI 10.17487/RFC7228, May 2014,

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   [RFC7252]  Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
              Application Protocol (CoAP)", RFC 7252,
              DOI 10.17487/RFC7252, June 2014,

   [RFC7575]  Behringer, M., Pritikin, M., Bjarnason, S., Clemm, A.,
              Carpenter, B., Jiang, S., and L. Ciavaglia, "Autonomic
              Networking: Definitions and Design Goals", RFC 7575,
              DOI 10.17487/RFC7575, June 2015,

   [RFC7589]  Badra, M., Luchuk, A., and J. Schoenwaelder, "Using the
              NETCONF Protocol over Transport Layer Security (TLS) with
              Mutual X.509 Authentication", RFC 7589,
              DOI 10.17487/RFC7589, June 2015,

   [RFC7950]  Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
              RFC 7950, DOI 10.17487/RFC7950, August 2016,

   [RFC7951]  Lhotka, L., "JSON Encoding of Data Modeled with YANG",
              RFC 7951, DOI 10.17487/RFC7951, August 2016,

   [RFC8040]  Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
              Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,

   [RFC8199]  Bogdanovic, D., Claise, B., and C. Moberg, "YANG Module
              Classification", RFC 8199, DOI 10.17487/RFC8199, July
              2017, <>.

   [RFC8294]  Liu, X., Qu, Y., Lindem, A., Hopps, C., and L. Berger,
              "Common YANG Data Types for the Routing Area", RFC 8294,
              DOI 10.17487/RFC8294, December 2017,

   [RFC8341]  Bierman, A. and M. Bjorklund, "Network Configuration
              Access Control Model", STD 91, RFC 8341,
              DOI 10.17487/RFC8341, March 2018,

   [RFC8342]  Bjorklund, M., Schoenwaelder, J., Shafer, P., Watsen, K.,
              and R. Wilton, "Network Management Datastore Architecture
              (NMDA)", RFC 8342, DOI 10.17487/RFC8342, March 2018,

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   [RFC8368]  Eckert, T., Ed. and M. Behringer, "Using an Autonomic
              Control Plane for Stable Connectivity of Network
              Operations, Administration, and Maintenance (OAM)",
              RFC 8368, DOI 10.17487/RFC8368, May 2018,

   [RFC8639]  Voit, E., Clemm, A., Gonzalez Prieto, A., Nilsen-Nygaard,
              E., and A. Tripathy, "Subscription to YANG Notifications",
              RFC 8639, DOI 10.17487/RFC8639, September 2019,

   [RFC8641]  Clemm, A. and E. Voit, "Subscription to YANG Notifications
              for Datastore Updates", RFC 8641, DOI 10.17487/RFC8641,
              September 2019, <>.

   [RFC8990]  Bormann, C., Carpenter, B., Ed., and B. Liu, Ed., "GeneRic
              Autonomic Signaling Protocol (GRASP)", RFC 8990,
              DOI 10.17487/RFC8990, May 2021,

   [RFC8993]  Behringer, M., Ed., Carpenter, B., Eckert, T., Ciavaglia,
              L., and J. Nobre, "A Reference Model for Autonomic
              Networking", RFC 8993, DOI 10.17487/RFC8993, May 2021,

   [RFC9113]  Thomson, M., Ed. and C. Benfield, Ed., "HTTP/2", RFC 9113,
              DOI 10.17487/RFC9113, June 2022,

   [RFC9171]  Burleigh, S., Fall, K., and E. Birrane, III, "Bundle
              Protocol Version 7", RFC 9171, DOI 10.17487/RFC9171,
              January 2022, <>.

   [RFC9172]  Birrane, III, E. and K. McKeever, "Bundle Protocol
              Security (BPSec)", RFC 9172, DOI 10.17487/RFC9172, January
              2022, <>.

   [RFC9254]  Veillette, M., Ed., Petrov, I., Ed., Pelov, A., Bormann,
              C., and M. Richardson, "Encoding of Data Modeled with YANG
              in the Concise Binary Object Representation (CBOR)",
              RFC 9254, DOI 10.17487/RFC9254, July 2022,

              World Wide Web Consortium, "XML Information Set (Second
              Edition)", February 2004,

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   [XPath]    World Wide Web Consortium, "XML Path Language (XPath)
              Version 1.0", November 1999,


   Brian Sipos of the Johns Hopkins University Applied Physics
   Laboratory (JHU/APL) provided excellent technical review of the DTNMA
   concepts presented in this document and additional information
   related to existing network management techniques.

Authors' Addresses

   Edward J. Birrane
   Johns Hopkins Applied Physics Laboratory

   Sarah E. Heiner
   Johns Hopkins Applied Physics Laboratory

   Emery Annis
   Johns Hopkins Applied Physics Laboratory

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