Delay-Tolerant Networking                                     E. Birrane
Internet-Draft                  Johns Hopkins Applied Physics Laboratory
Intended status: Informational                            August 7, 2019
Expires: February 8, 2020

                  Asynchronous Management Architecture


   This document describes an asynchronous management architecture (AMA)
   suitable for providing application-level network management services
   in a challenged networking environment.  Challenged networks are
   those that require fault protection, configuration, and performance
   reporting while unable to provide humans-in-the-loop with synchronous
   feedback or otherwise preserve transport-layer sessions.  In such a
   context, networks must exhibit behavior that is both determinable and
   autonomous while maintaining compatibility with existing network
   management protocols and operational concepts.

Status of This Memo

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   This Internet-Draft will expire on February 8, 2020.

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   to this document.  Code Components extracted from this document must
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.2.  Requirements Language . . . . . . . . . . . . . . . . . .   4
     1.3.  Organization  . . . . . . . . . . . . . . . . . . . . . .   4
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   5
   3.  Motivation  . . . . . . . . . . . . . . . . . . . . . . . . .   6
     3.1.  Challenged Networks . . . . . . . . . . . . . . . . . . .   7
     3.2.  Current Approaches and Their Limitations  . . . . . . . .   8
   4.  Service Definitions . . . . . . . . . . . . . . . . . . . . .   9
     4.1.  Configuration . . . . . . . . . . . . . . . . . . . . . .   9
     4.2.  Reporting . . . . . . . . . . . . . . . . . . . . . . . .  10
     4.3.  Autonomous Parameterized Procedure Calls  . . . . . . . .  10
     4.4.  Administration  . . . . . . . . . . . . . . . . . . . . .  11
   5.  Desirable Properties  . . . . . . . . . . . . . . . . . . . .  12
     5.1.  Intelligent Push of Information . . . . . . . . . . . . .  12
     5.2.  Minimize Message Size Not Node Processing . . . . . . . .  12
     5.3.  Absolute Data Identification  . . . . . . . . . . . . . .  13
     5.4.  Custom Data Definition  . . . . . . . . . . . . . . . . .  13
     5.5.  Autonomous Operation  . . . . . . . . . . . . . . . . . .  13
   6.  Roles and Responsibilities  . . . . . . . . . . . . . . . . .  14
     6.1.  Agent Responsibilities  . . . . . . . . . . . . . . . . .  14
     6.2.  Manager Responsibilities  . . . . . . . . . . . . . . . .  15
   7.  Logical Data Model  . . . . . . . . . . . . . . . . . . . . .  16
     7.1.  Data Representations: Constants, Externally Defined Data,
           and Variables . . . . . . . . . . . . . . . . . . . . . .  16
     7.2.  Data Collections: Reports and Tables  . . . . . . . . . .  17
       7.2.1.  Report Templates and Reports  . . . . . . . . . . . .  17
       7.2.2.  Table Templates and Tables  . . . . . . . . . . . . .  18
     7.3.  Command Execution: Controls and Macros  . . . . . . . . .  18
     7.4.  Autonomy: Time and State-Based Rules  . . . . . . . . . .  19
       7.4.1.  State-Based Rule (SBR)  . . . . . . . . . . . . . . .  19
       7.4.2.  Time-Based Rule (TBR) . . . . . . . . . . . . . . . .  20
     7.5.  Calculations: Expressions, Literals, and Operators  . . .  20
   8.  System Model  . . . . . . . . . . . . . . . . . . . . . . . .  21
     8.1.  Control and Data Flows  . . . . . . . . . . . . . . . . .  21
     8.2.  Control Flow by Role  . . . . . . . . . . . . . . . . . .  22
       8.2.1.  Notation  . . . . . . . . . . . . . . . . . . . . . .  22
       8.2.2.  Serialized Management . . . . . . . . . . . . . . . .  22
       8.2.3.  Multiplexed Management  . . . . . . . . . . . . . . .  23
       8.2.4.  Data Fusion . . . . . . . . . . . . . . . . . . . . .  25
   9.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  26

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   10. Security Considerations . . . . . . . . . . . . . . . . . . .  26
   11. Informative References  . . . . . . . . . . . . . . . . . . .  26
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  27

1.  Introduction

   The Asynchronous Management Architecture (AMA) provides application-
   layer network management services over links where delivery delays
   prevent timely communications between a network operator and a
   managed device.  These delays may be caused by long signal
   propagations or frequent link disruptions (such as described in
   [RFC4838]) or by non-environmental factors such as unavailability of
   network operators, administrative delays, or delays caused by
   quality-of-service prioritizations and service-level agreements.

   An AMA is necessary as the assumptions inherent to the architecture
   and design of synchronous management tools and techniques are not
   valid in challenged network scenarios.  In these scenarios,
   synchronous approaches either patiently wait for periods of bi-
   directional connectivity or require the investment of significant
   time and resources to evolve a challenged network into a well-
   connected, low-latency network.  In some cases such evolution is
   merely a costly way to over-resource a network.  In other cases, such
   evolution is impossible given physical limitations imposed by signal
   propagation delays, power, transmission technologies, and other
   phenomena.  Asynchronous management of asynchronous networks enables
   large-scale deployments, distributed technical capabilities, and
   reduced deployment and operations costs.

   The rationale and motivation for asynchronous management is captured
   in [BIRRANE1], [BIRRANE2],[BIRRANE3].  The properties and feasibility
   of such a system are taken from prototyping work done in accordance
   with [I-D.irtf-dtnrg-dtnmp].

1.1.  Scope

   This document describes the motivation, service definitions,
   desirable properties, roles/responsibilities, system model, and
   logical data model that form the AMA.  These descriptions should be
   of sufficient specificity that implementations conformant to this
   architecture will operate successfully in a challenged networking

   This document is not a prescriptive standardization of a physical
   data model or protocol.  Instead, it serves as informative guidance
   to authors of such models and protocols.

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   It is assumed that any challenged network where network management
   would be usefully applied supports basic services (where necessary)
   such as naming, addressing, integrity, confidentiality,
   authentication, fragmentation, and traditional network/session layer
   functions.  Therefore, these items are outside of the scope of the
   AMA and not covered in this document.

   While possible that a challenged network may interface with an
   unchallenged network, this document does not address the concept of
   network management compatibility with synchronous approaches.

1.2.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in [RFC2119].

1.3.  Organization

   The remainder of this document is organized into seven sections that,
   together, describe an AMA suitable for enterprise management of
   asynchronous networks: terminology, motivation, service definitions,
   desirable properties, roles/responsibilities, logical data model, and
   system model.  The description of each section is as follows.

   o  Terminology - This section identifies those terms critical to
      understanding the proper operation of the AMA.  Whenever possible,
      these terms align in both word selection and meaning with their
      analogs from other management protocols.

   o  Motivation - This section provides an overall motivation for this
      work as providing a novel and useful alternative to current
      network management approaches.  Specifically, this section
      describes common network functions and how synchronous mechanisms
      fail to provide these functions in an asynchronous environment.

   o  Service Definitions - This section defines asynchronous network
      management services in terms of terminology, scope, and impact.

   o  Desirable Properties - This section identifies the properties to
      which an asynchronous management system should adhere to
      effectively implement service definitions in an asynchronous
      environment.  These properties guide the subsequent definition of
      the system and logical models that comprise the AMA.

   o  Roles and Responsibilities - This section identifies the roles in
      the AMA and their associated responsibilities.  It provides the

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      terminology and context for discussing how network management
      services interact.

   o  Logical Data Model - This section describes the kinds of data that
      should be represented in deployment asynchronous management

   o  System Model - This section describes data flows amongst various
      defined Actor roles.  These flows capture how the AMA system works
      to provide asynchronous network management services in accordance
      with defined desirable properties.

2.  Terminology

   o  Actor - A software service running on either managed or managing
      devices for the purpose of implementing management protocols
      between such devices.  Actors may implement the "Manager" role,
      "Agent" role, or both.

   o  Agent Role (or Agent) - The role associated with a managed device,
      responsible for reporting performance data, enforcing
      administrative policies, and accepting/performing actions.  Agents
      exchange information with Managers operating either on the same
      device or on a remote managing device.

   o  Externally Defined Data (EDD) - Information made available to an
      Agent by a managed device, but not computed directly by the Agent.

   o  Variables (VARs) - Information that is computed by an Agent,
      typically as a function of EDD values and/or other Variables.

   o  Constants (CONST) - A constant represents a typed, immutable value
      that is referred to by a semantic name.  Constants are used in
      situations where substituting a name for a fixed value provides
      useful semantic information.  For example, using the named
      constant PI rather than the literal value 3.14.

   o  Controls (CTRLs) - Operations that may be undertaken by an Actor
      to change the behavior, configuration, or state of an application
      or protocol managed by an AMP.

   o  Literals (LITs) - A literal represents a value without a semantic
      name.  Literals are used in cases where adding a semantic name to
      a fixed value provides no useful semantic information.  For
      example, the number 4 is a literal value.

   o  Macros (MACs) - A named, ordered collection of Controls.

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   o  Manager - A role associated with a managing device responsible for
      configuring the behavior of, and receiving information from,
      Agents.  Managers interact with one or more Agents located on the
      same device and/or on remote devices in the network.

   o  Operator (OP) - The enumeration and specification of a
      mathematical function used to calculate variable values and
      construct expressions to evaluate Agent state.

   o  Report (RPT) - A typed, ordered collection of data values gathered
      by one or more Agents and provided to one or more Managers.
      Reports only contain typed data values and the identity of the
      Report Template (RPTT) to which they conform.

   o  Report Template (RPTT) - A named, typed, ordered collection of
      data types that represent the structure of a Report (RPT).  This
      is the schema for a Report, generated by a Manager and
      communicated to one or more Agents.

   o  Rule - A unit of autonomous specification that provides a
      stimulus-response relationship between time or state on an Agent
      and the Controls to be run as a result of that time or state.

   o  State-Based Rule (SBR) - A state-based rule is any rule in which
      the rule stimulus is triggered by the calculable internal state of
      the Agent.

   o  Table (TBL) - A typed collection of data values organized in a
      tabular way in which columns represent homogeneous types of data
      and rows represent unique sets of data values conforming to column
      types.  Reports only contain typed data values and the identity of
      the Table Template (TBLT) to which they confirm.

   o  Table Template (TBLT) - A named, typed, ordered collection of
      columns that comprise the structure for representing tabular data
      values.  This template forms the structure of a Table (TBL).

   o  Time-Based Rule (TBR) - A time-based rule is a specialization, and
      simplification, of a state-based rule in which the rule stimulus
      only considers relative time as it is known on the Agent.

3.  Motivation

   Challenged networks, to include networks challenged by administrative
   or policy delays, cannot guarantee capabilities required to enable
   synchronous management techniques.  These capabilities include high-
   rate, highly-available data, round-trip data exchange, and operators
   "in-the-loop".  The inability of current approaches to provide

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   network management services in a challenged network motivates the
   need for a new network management architecture focused on
   asynchronous, open-loop, autonomous control of network components.

3.1.  Challenged Networks

   A growing variety of link-challenged networks support packetization
   to increase data communications reliability without otherwise
   guaranteeing a simultaneous end-to-end path.  Examples of such
   networks include Mobile Ad-Hoc Networks (MANets), Vehicular Ad-Hoc
   Networks (VANets), Space-Terrestrial Internetworks (STINTs), and
   heterogeneous networking overlays.  Links in such networks are often
   unavailable due to attenuations, propagation delays, occultation, and
   other limitations imposed by energy and mass considerations.  Data
   communications in such networks rely on store-and-forward and other
   queuing strategies to wait for the connectivity necessary to usefully
   advance a packet along its route.

   Similarly, there also exist well-resourced networks that incur high
   message delivery delays due to hardware, software, or human
   limitations.  Some examples of these networks are networks with
   understaffed operations centers and where data volume and management
   requirements exceed the real-time cognitive load of operators and/or
   their associated operations console software support.  Also, networks
   that restrict user access to existing bandwidth due to policy create
   functionally similar situations to that of link disruption and delay.

   Independent of the reason, when a node experiences an inability to
   communicate it must rely on autonomous mechanisms to ensure its safe
   operation and ability to usefully re-join the network at a later
   time.  Additionally, nodes in a sparsely populated network may often
   be disconnected, making the concepts of "connected network" and
   "instantaneous connectivity" either impractical or impossible.

   Specifically, challenged networks exhibit the following properties
   that may violate assumptions built into current approaches to
   synchronous network management.

   o  Links may be uni-directional.

   o  Bi-directional links may have asymmetric data rates.

   o  No end-to-end path is guaranteed to exist at any given time
      between any two nodes.

   o  Round-trip communications between any two nodes within any given
      time window may be impossible.

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3.2.  Current Approaches and Their Limitations

   Network management tools in unchallenged networks provide mechanisms
   for communicating locally-collected data from Agents to Managers,
   typically using a "pull" mechanism where data must be explicitly
   requested by a Manager in order to be transmitted by an Agent.

   Management approaches that rely on timely data exchange, such as
   those that rely on negotiated sessions or other synchronized
   acknowledgment, do not function in challenged network environments.
   Familiar examples of TCP/IP based management via closed-loop,
   synchronous messaging do not work when network disruptions increase
   in frequency and severity.  While no protocol delivers data in the
   absence of a networking link, protocols that eliminate or drastically
   reduce overhead and end-point coordination require smaller
   transmission windows and continue to function when confronted with
   scaling delays and disruptions in the network.

   A legacy method for management in unchallenged networks today is the
   Simple Network Management Protocol (SNMP) [RFC3416].  SNMP utilizes a
   request/response model to set and retrieve data values such as host
   identifiers, link utilizations, error rates, and counters between
   application software on Agents and Managers.  Data may be directly
   sampled or consolidated into representative statistics.
   Additionally, SNMP supports a model for asynchronous notification
   messages, called traps, based on predefined triggering events.  Thus,
   Managers can query Agents for status information, send new
   configurations, and be informed when specific events have occurred.
   Traps and queryable data are defined in one or more Managed
   Information Bases (MIBs) which define the information for a
   particular data standard, protocol, device, or application.

   While there is a large installation base for SNMP there are several
   aspects of the protocol that make in inappropriate for use in a
   challenged networking environment.  SNMP relies on sessions with low
   round-trip latency to support its "pull" model.  The SNMP trap model
   provides some Agent-side processing, however because the processing
   has very low fidelity and traps are typically "fire and forget," the
   underlying transport protocol that supports reliable, in-order
   message delivery is required.  Adaptive modifications to SNMP to
   support challenged networks would alter the basic function of the
   protocol (data models, control flows, and syntax) so as to be
   functionally incompatible with existing SNMP installations.
   Therefore, this approach is not suitable for an asynchronous network
   management system.

   The Network Configuration Protocol (NETCONF) provides device-level
   configuration capabilities [RFC6241] to replace vendor-specific

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   command line interface configuration software.  The XML-based
   protocol provides a remote procedure call (RPC) syntax such that any
   exposed functionality on an Agent can be exercised via a software
   application interface.  NETCONF places no specific functional
   requirements or constraints on the capabilities of the Agent, which
   makes it a very flexible tool for configuring a homogeneous network
   of devices.

   NETCONF places specific constraints on any underlying transport
   protocol: a long-lived, reliable, low-latency sequenced data delivery
   session.  This is a fundamental requirement given the RPC-nature of
   the operating concept, and it is unsustainable in a challenged
   network.  Aspects of the data modeling associated with NETCONF may
   apply to an asynchronous network management system, such that some
   modeling tools may be used, even if the network control plane cannot.

   Just as the concept of a loosely-confederated set of nodes changes
   the definition of a network, it also changes the operational concept
   of what it means to manage a network.  When a network stops being a
   single entity exhibiting a single behavior, "network management"
   becomes large-scale "node management".  Individual nodes must share
   the burden of implementing desirable behavior without reliance on a
   single oracle of configuration or other coordinating function such as
   an operator-in-the-loop.

4.  Service Definitions

   This section identifies the services that must exist between Managers
   and Agents within an AMA.  These services include configuration,
   reporting, parameterized control, and administration.

4.1.  Configuration

   Configuration services update Agent data associated with managed
   applications and protocols.  Some configuration data might be defined
   in the context of an application or protocol, such that any network
   using that application or protocol would understand that data.  Other
   configuration data may be defined tactically for use in a specific
   network deployment and not available to other networks even if they
   use the same applications or protocols.

   New configurations received by an Agent must be validated to ensure
   that they do not conflict with other configurations or would
   otherwise prevent the Agent from effectively working with other
   Actors in its region.  With no guarantee of round-trip data exchange,
   Agents cannot rely on remote Managers to correct erroneous or stale
   configurations from harming the flow of data through a challenged

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   Examples of configuration service behavior include the following.

   o  Creating a new datum as a function of other well-known data:
      C = A + B.

   o  Creating a new report as a unique, ordered collection of known
      RPT = {A, B, C}.

   o  Storing predefined, parameterized responses to potential future
      IF (X > 3) THEN RUN CMD(PARM).

4.2.  Reporting

   Reporting services populate report templates with values collected or
   computed by an Agent.  The resultant reports are sent to one or more
   Managers by the Agent.  The term "reporting" is used in place of the
   term "monitoring", as monitoring implies a timeliness and regularity
   that cannot be guaranteed by a challenged network.  Reports sent by
   an Agent provide best-effort information to receiving Managers.

   Since a Manager is not actively "monitoring" an Agent, the Agent must
   make its own determination on when to send what Reports based on its
   own local time and state information.  Agents should produce Reports
   of varying fidelity and with varying frequency based on thresholds
   and other information set as part of configuration services.

   Examples of reporting service behavior include the following.

   o  Generate Report R1 every hour (time-based production).

   o  Generate Report R2 when X > 3 (state-based production).

4.3.  Autonomous Parameterized Procedure Calls

   Similar to an RPC call, some mechanism MUST exist which allows a
   procedure to be run on an Agent in order to effect its behavior or
   otherwise change its internal state.  Since there is no guarantee
   that a Manager will be in contact with an Agent at any given time,
   the decisions of whether and when a procedure should be run MUST be
   made locally and autonomously by the Agent.  Two types of automation
   triggers are identified in the AMA: triggers based on the general
   state of the Agent and triggers based on an Agent's notion of time.
   As such, the autonomous execution of procedures can be viewed as a
   stimulus-response system, where the stimulus is the positive
   evaluation of a state or time based predicate and the response is the
   function to be executed.

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   The autonomous nature of procedure execution by an Agent implies that
   the full suite of information necessary to run a procedure may not be
   known by a Manager in advance.  To address this situation, a
   parameterization mechanism MUST be available so that required data
   can be provided at the time of execution on the Agent rather than at
   the time of definition/configuration by the Manager.

   Autonomous, parameterized procedure calls provide a powerful
   mechanism for Managers to "manage" an Agent asynchronously during
   periods of no communication by pre-configuring responses to events
   that may be encountered by the Agent at a future time.

   Examples of potential behavior include the following.

   o  Updating local routing information based on instantaneous link

   o  Managing storage on the device to enforce quotas.

   o  Applying or modifying local security policy.

4.4.  Administration

   Administration services enforce the potentially complex mapping of
   configuration, reporting, and control services amongst Agents and
   Managers in the network.  Fine-grained access controls that specify
   which Managers may apply which services to which Agents may be
   necessary in networks that either deal with multiple administrative
   entities or overlay networks that cross administrative boundaries.
   Whitelists, blacklists, key-based infrastructures, or other schemes
   may be used for this purpose.

   Examples of administration service behavior include the following.

   o  Agent A1 only Sends reports for Protocol P1 to Manager M1.

   o  Agent A2 only accepts a configurations for Application Y from
      Managers M2 and M3.

   o  Agent A3 accepts services from any Manager providing the proper
      authentication token.

   Note that the administrative enforcement of access control is
   different from security services provided by the networking stack
   carrying AMP messages.

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5.  Desirable Properties

   This section describes those design properties that are desirable
   when defining an architecture that must operate 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 AMA.

5.1.  Intelligent Push of Information

   Pull management mechanisms require that a Manager send a query to an
   Agent and then wait for the response to that query.  This practice
   implies a control-session between entities and increases the overall
   message traffic in the network.  Challenged networks cannot guarantee
   that the roundtrip data-exchange will occur in a timely fashion.  In
   extreme cases, networks may be comprised of solely uni-directional
   links which drastically increases the amount of time needed for a
   roundtrip data exchange.  Therefore, pull mechanisms must be avoided
   in favor of push mechanisms.

   Push mechanisms, in this context, refer to the ability of Agents to
   make their own determinations in relation to the information that
   should be sent to Managers.  Such mechanisms do not require round-
   trip communications as Managers do not request each reporting
   instance; Managers need only request once, in advance, that
   information be produced in accordance with a predetermined schedule
   or in response to a predefined state on the Agent.  In this way
   information is "pushed" from Agents to Managers and the push is
   "intelligent" because it is based on some internal evaluation
   performed by the Agent.

5.2.  Minimize Message Size Not Node Processing

   Protocol designers must balance message size versus message
   processing time at sending and receiving nodes.  Verbose
   representations of data simplify node processing whereas compact
   representations require additional activities to generate/parse the
   compacted message.  There is no asynchronous management advantage to
   minimizing node processing time in a challenged network.  However,
   there is a significant advantage to smaller message sizes in such
   networks.  Compact messages require smaller periods of viable
   transmission for communication, incur less re-transmission cost, and
   consume less resources when persistently stored en-route in the
   network.  AMPs should minimize PDUs whenever practical, to include
   packing and unpacking binary data, variable-length fields, and pre-
   configured data definitions.

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5.3.  Absolute Data Identification

   Elements within the management system must be uniquely identifiable
   so that they can be individually manipulated.  Identification schemes
   that are relative to system configuration make data exchange between
   Agents and Managers difficult as system configurations may change
   faster than nodes can communicate.

   Consider the following common technique for approximating an
   associative array lookup.  A manager wishing to do an associative
   lookup for some key K1 will (1) query a list of array keys from the
   agent, (2) find the key that matches K1 and infer the index of K1
   from the returned key list, and (3) query the discovered index on the
   agent to retrieve the desired data.

   Ignoring the inefficiency of two pull requests, this mechanism fails
   when the Agent changes its key-index mapping between the first and
   second query.  Rather than constructing an artificial mapping from K1
   to an index, an AMP must provide an absolute mechanism to lookup the
   value K1 without an abstraction between the Agent and Manager.

5.4.  Custom Data Definition

   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
   possible.  Specifically, an Agent should not be required to transmit
   a large data set for a Manager that only wishes to calculate a
   smaller, inferred data set.  The Agent should calculate the smaller
   data set on its own and transmit that instead.  Since the
   identification of custom data sets is likely to occur in the context
   of a specific network deployment, AMPs must provide a mechanism for
   their definition.

5.5.  Autonomous Operation

   AMA network functions must be achievable using only knowledge local
   to the Agent.  Rather than directly controlling an Agent, a Manager
   configures an engine of the Agent to take its own action under the
   appropriate conditions in accordance with the Agent's notion of local
   state and time.

   Such an engine 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.
   Wholly autonomous operations MAY be supported where required.
   Generally, autonomous operations should provide the following

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   o  Distributed Operation - The concept of pre-configuration allows
      the Agent to operate without regular contact with Managers in the
      system.  The initial configuration (and periodic update) of the
      system remains difficult in a challenged network, but an initial
      synchronization on stimuli and responses drastically reduces needs
      for centralized operations.

   o  Deterministic Behavior - Such behavior is necessary in critical
      operational systems where the actions of a platform must be well
      understood even in the absence of an operator in the loop.
      Depending on the types of stimuli and responses, these systems may
      be considered to be maintaining simple automation or semi-
      autonomous behavior.  In either case, this preserves the ability
      of a frequently-out-of-contact Manager to predict the state of an
      Agent with more reliability than cases where Agents implement
      independent and fully autonomous systems.

   o  Engine-Based Behavior - Several operational systems are unable to
      deploy "mobile code" based solutions due to network bandwidth,
      memory or processor loading, or security concerns.  Engine-based
      approaches are preferred as they can be flexible without incurring
      a set of problematic requirements or concerns.

6.  Roles and Responsibilities

   By definition, Agents reside on managed devices and Managers reside
   on managing devices.  This section describes how these roles
   participate in the network management functions outlined in the prior

6.1.  Agent Responsibilities

   Application Support
           Agents MUST collect all data, execute all procedures,
           populate all reports and run operations required by each
           application which the Agent claims to manage.  Agents MUST
           report supported applications so that Managers in a network
           understands what information is understood by what Agent.

   Local Data Collection
           Agents MUST collect from local firmware (or other on-board
           mechanisms) and report all data defined for the management of
           applications for which they have been configured.

   Autonomous Control
           Agents MUST determine, without Manager intervention, whether
           a procedure should be invoked.  Agents MAY also invoke
           procedures on other devices for which they act as proxy.

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   User Data Definition
           Agents MUST provide mechanisms for operators in the network
           to use configuration services to create customized data
           definitions in the context of a specific network or network
           use-case.  Agents MUST allow for the creation, listing, and
           removal of such definitions in accordance with whatever
           security models are deployed within the particular network.

           Where applicable, Agents MUST verify the validity of these
           definitions when they are configured and respond in a way
           consistent with the logging/error-handling policies of the
           Agent and the network.

   Autonomous Reporting
           Agents MUST determine, without real-time Manager
           intervention, whether and when to populate and transmit a
           given report targeted to one or more Managers in the network.

   Consolidate Messages
           Agents SHOULD produce as few messages as possible when
           sending information.  For example, rather than sending
           multiple messages, each with one report to a Manager, an
           Agent SHOULD prefer to send a single message containing
           multiple reports.

   Regional Proxy
           Agents MAY perform any of their responsibilities on behalf of
           other network nodes that, themselves, do not have an Agent.
           In such a configuration, the Agent acts as a proxy for these
           other network nodes.

6.2.  Manager Responsibilities

   Agent Capabilities Mapping
           Managers MUST understand what applications are managed by the
           various Agents with which they communicate.  Managers should
           not attempt to request, invoke, or refer to application
           information for applications not managed by an Agent.

   Data Collection
           Managers MUST receive information from Agents by
           asynchronously configuring the production of reports and then
           waiting for, and collecting, responses from Agents over time.
           Managers MAY try to detect conditions where Agent information
           has not been received within operationally relevant time
           spans and react in accordance with network policy.

   Custom Definitions

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           Managers should provide the ability to define custom data
           definitions.  Any custom definitions MUST be transmitted to
           appropriate Agents and these definitions MUST be remembered
           to interpret the reporting of these custom values from Agents
           in the future.

   Data Translation
           Managers should provide some interface to other network
           management protocols.  Managers MAY accomplish this by
           accumulating a repository of push-data from high-latency
           parts of the network from which data may be pulled by low-
           latency parts of the network.

   Data Fusion
           Managers MAY support the fusion of data from multiple Agents
           with the purpose of transmitting fused data results to other
           Managers within the network.  Managers MAY receive fused
           reports from other Managers pursuant to appropriate security
           and administrative configurations.

7.  Logical Data Model

   The AMA logical data model captures the types of information that
   should be collected and exchanged to implement necessary roles and
   responsibilities.  The data model presented in this section does not
   presuppose a specific mapping to a physical data model or encoding
   technique; it is included to provide a way to logically reason about
   the types of data that should be exchanged in an asynchronously
   managed network.

   The elements of the AMA logical data model are described as follows.

7.1.  Data Representations: Constants, Externally Defined Data, and

   There are three fundamental representations of data in the AMA: (1)
   data whose values do not change as a function of time or state, (2)
   data whose values change as determined by sampling/calculation
   external to the network management system, and (3) data whose values
   are calculated internal to the network management system.

   Data whose values do not change as a function of time or state are
   defined as Constants (CONST).  CONST values are strongly types, named
   values that cannot be modified once they have been defined.

   Data that are sampled/calculated external to the network management
   system are defined as Externally Defined Data" (EDD).  EDD values
   represent the most useful information in the management system as

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   they are provided by the applications or protocols being managed on
   the Agent.  It is RECOMMENDED that EDD values be strongly typed to
   avoid issues with interpreting the data value.  It is also
   RECOMMENDED that the timeliness/staleness of the data value be
   considered when using the data in the context of autonomous action on
   the Agent.

   Data that is calculated internal to the network management system is
   defined as a Variable (VAR).  VARs allow the creation of new data
   values for use in the network management system.  New value
   definitions are useful for storing user-defined information, storing
   the results of complex calculations for easier re-use, and providing
   a mechanism for combining information from multiple external sources.
   It is RECOMMENDED that VARs be strongly typed to avoid issues with
   interpreting the data value.  In cases where a VAR definition relies
   on other VAR definitions, mechanisms to prevent circular references
   MUST be included in any actual data model or implementation.

7.2.  Data Collections: Reports and Tables

   Individual data values may be exchanged amongst Agents and Managers
   in the AMA.  However, data are typically most useful to a Manager
   when received as part of a set of information.  Ordered collections
   of data values can be produced by Agents and sent to Managers as a
   way of efficiently communicating Agent status.  Within the AMA, the
   structure of the ordered collection is treated separately from the
   values that populate such a structure.

   The AMA provides two ways of defining collections of data: reports
   and tables.  Reports are ordered sets of data values, whereas Tables
   are special types of reports whose entries have a regular, tabular

7.2.1.  Report Templates and Reports

   The typed, ordered structure of a data collection is defined as a
   Report Template (RPTT).  A particular set of data values provided in
   compliance with such a template is called a Report (RPT).

   Separating the structure and content of a report reduces the overall
   size of RPTs in cases where reporting structures are well known and
   unchanging.  RPTTs can be synchronized between an Agent and a Manager
   so that RPTs themselves do not incur the overhead of carrying self-
   describing data.  RPTTs may include EDD values, VARs, and also other
   RPTTs.  In cases where a RPTT includes another RPTTs, mechanisms to
   prevent circular references MUST be included in any actual data model
   or implementation.

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   Protocols and applications managed in the AMA may define common
   RPTTs.  Additionally, users within a network may define their own
   RPTTs that are useful in the context of a particular deployment.

7.2.2.  Table Templates and Tables

   Tables optimize the communication of multiple sets of data in
   situations where each data set has the same syntactical structure and
   with the same semantic meaning.  Unlike reports, the regularity of
   tabular data representations allow for the addition of new rows
   without changing the structure of the table.  Attempting to add a new
   data set at the end of a report would require alterations to the
   report template.

   The typed, ordered structure of a table is defined as a
   Table Template (TBLT).  A particular instance of values populating
   the table template is called a Table (TBL).

   TBLTs describes the "columns" that define the table schema.  A TBL
   represents the instance of a specific TBLT that holds actual data
   values.  These data values represent the "rows" of the table.

   The prescriptive nature of the TBLT allows for the possibility of
   advanced filtering which may reduce traffic between Agents and
   Managers.  However, the unique structure of each TBLT may make them
   difficult or impossible to change dynamically in a network.

7.3.  Command Execution: Controls and Macros

   Low-latency, high-availability approaches to network management use
   mechanisms such as (or similar to) RPCs to cause some action to be
   performed on an Agent.  The AMA enables similar capabilities without
   requiring that the Manager be in the processing loop of the Agent.
   Command execution in the AMA happens through the use of controls and

   A Control (CTRL) represents a parameterized, predefined procedure
   that can be run on an Agent.  CTRLs do not have a return code as
   there is not the same concept of sequential execution in an
   asynchronous model.  Parameters can be provided when running a
   command from a Manager, pre-configured as part of an autonomy
   response on the Agent, or auto-generated as needed on the Agent.  The
   success or failure of a control MAY be inferred by reports generated
   for that purpose.

   NOTE: The AMA term control is derived in part from the concept of
   Command and Control (C2) where control implies the operational
   instructions that must be undertaken to implement (or maintain) a

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   commanded objective.  An asynchronous management function controls an
   Agent to allow it to fulfill its commanded purpose in a variety of
   operational scenarios.  For example, attempting to maintain a safe
   internal thermal environment for a spacecraft is considered "thermal
   control" (not "thermal commanding") even though thermal control
   involves "commanding" heaters, louvers, radiators, and other
   temperature-effecting components.

   Often, a series of controls must be executed in concert to achieve a
   particular outcome.  A Macro (MACRO) represents an ordered collection
   of controls (or other macros).  In cases where a MACRO includes
   another MACRO, mechanisms to prevent circular references and maximum
   nesting levels MUST be included in any actual data model or

7.4.  Autonomy: Time and State-Based Rules

   The AMA data model contains EDDs and VARs that capture the state of
   applications on an Agent.  The model also contains controls and
   macros to perform actions on an Agent.  A mechanism is needed to
   relate these two capabilities: to perform an action on the Agent in
   response to the state of the Agent.  This mechanism in the AMA is the
   "rule" and can key activated based on Agent state (state-based rule)
   or based on the Agent's notion of relative time (time-based rule).

7.4.1.  State-Based Rule (SBR)

   State-Based Rules (SBRs) perform actions based on the Agent's
   internal state, as identified by EDD and VAR values.  An SBR
   represents a stimulus-response pairing in the following form:

   IF predicate THEN response

   The predicate is a logical expression that evaluates to true if the
   rule stimulus is present and evaluates to false otherwise.  The
   response may be any control or macro known to the Agent.

   An example of an SBR could be to turn off a heater if some internal
   temperature is greater than a threshold:

   IF (current_temp > maximum_temp) THEN turn_heater_off

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   Rules should be allowed to construct their stimuli from the full set
   of EDD values and VARs available to the network management system.
   Similarly, macro responses should be allowed to include controls from
   all applications known by the Agent.  This enables an expressive
   capability to have multiple applications monitored and managed by the

7.4.2.  Time-Based Rule (TBR)

   Time-Based Rules (TBR) perform actions based on the Agent's notion of
   the passage of time.  A possible TBR construct would be to perform
   some action at 1Hz on the Agent.

   A TBR is a specialization of an SBR as the Agent's notion of time is
   a type of Agent state.  For example, a TBR to perform an action every
   24 hours could be expressed using some type of predicate of the form:

   (((current_time - base_time) % 24_hours) == 0)

   However, time-based events are popular enough that special semantics
   for expressing them would likely significantly reduce the
   computations necessary to represent time functions in a SBR.

7.5.  Calculations: Expressions, Literals, and Operators

   Actions such as computing a VAR value or describing a rule predicate
   require some mechanism for calculating the value of mathematical
   expressions.  In addition the the aforementioned AMA logical data
   objects, Literals, Operators, and Expressions are used to perform
   these calculations.

   A Literal (LIT) represents a strongly typed datum whose identity is
   equivalent to its value.  An example of a LIT value is "4" - it's
   identifier (4) is the same as its value (4).  Literals differ from
   constants in that constants have an identifier separate from their
   value.  For example, the constant PI may refer to a value of 3.14.
   However the literal 3.14159 always refers to the value 3.14159.

   An Operator (OP) represents a mathematical operation in an
   expression.  OPs should support multiple operands based on the
   operation supported.  A common set of OPs SHOULD be defined for any
   Agent and systems MAY choose to allow individual applications to
   define new OPs to assist in the generation of new VAR values and
   predicates for managing that application.  OPs may be simple binary
   operations such as "A + B" or more complex functions such as sin(A)
   or avg(A,B,C,D).  Additionally, OPs may be typed.  For example,

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   addition of integers may be defined separately from addition of real

   An Expression (EXPR) is a combination of operators and operands used
   to construct a numerical value from a series of other elements of the
   AMA logical model.  Operands include any AMA logical data model
   object that can be interpreted as a value, such as EDD, VAR, CONST,
   and LIT values.  Operators perform some function on operands to
   generate new values.

8.  System Model

   This section describes the notional data flows and control flows that
   illustrate how Managers and Agents within an AMA cooperate to perform
   network management services.

8.1.  Control and Data Flows

   The AMA identifies three significant data flows: control flows from
   Managers to Agents, reports flows from Agents to Managers, and fusion
   reports from Managers to other Managers.  These data flows are
   illustrated in Figure 1.

                        AMA Control and Data Flows

       +---------+       +------------------------+      +---------+
       | Node A  |       |         Node B         |      |  Node C |
       |         |       |                        |      |         |
       |+-------+|       |+-------+      +-------+|      |+-------+|
       ||       ||=====>>||Manager|====>>|       ||====>>||       ||
       ||       ||<<=====||   B   |<<====|Agent B||<<====||       ||
       ||       ||       |+--++---+      +-------+|      ||Manager||
       || Agent ||       +---||-------------------+      ||   C   ||
       ||   A   ||           ||                          ||       ||
       ||       ||<<=========||==========================||       ||
       ||       ||===========++========================>>||       ||
       |+-------+|                                       |+-------+|
       +---------+                                       +---------+

                                 Figure 1

   In this data flow, the Agent on node A receives Controls from
   Managers on nodes B and C, and replies with Report Entries back to
   these Managers.  Similarly, the Agent on node B interacts with the
   local Manager on node B and the remote Manager on node C.  Finally,
   the Manager on node B may fuse Report Entries received from Agents at
   nodes A and B and send these fused Report Entries back to the Manager
   on node C.

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   From this figure it is clear that there exist many-to-many
   relationships amongst Managers, amongst Agents, and between Agents
   and Managers.  Note that Agents and Managers are roles, not
   necessarily differing software applications.  Node A may represent a
   single software application fulfilling only the Agent role, whereas
   node B may have a single software application fulfilling both the
   Agent and Manager roles.  The specifics of how these roles are
   realized is an implementation matter.

8.2.  Control Flow by Role

   This section describes three common configurations of Agents and
   Managers and the flow of messages between them.  These configurations
   involve local and remote management and data fusion.

8.2.1.  Notation

   The notation outlined in Table 1 describes the types of control
   messages exchanged between Agents and Managers.

   |     Term    |              Definition              |   Example    |
   |     EDD#    |           EDD definition.            |     EDD1     |
   |             |                                      |              |
   |      V#     |         Variable definition.         | V1 = EDD1 +  |
   |             |                                      |     V0.      |
   |             |                                      |              |
   |  DEF([ACL], |   Define id from expression. Allow   | DEF([*], V1, |
   |   ID,EXPR)  |   managers in access control list    | EDD1 + EDD2) |
   |             |      (ACL) to request this id.       |              |
   |             |                                      |              |
   |  PROD(P,ID) | Produce ID according to predicate P. |   PROD(1s,   |
   |             |  P may be a time period (1s) or an   |    EDD1)     |
   |             |       expression (EDD1 > 10).        |              |
   |             |                                      |              |
   |   RPT(ID)   |      A report identified by ID.      |  RPT(EDD1)   |

                           Table 1: Terminology

8.2.2.  Serialized Management

   This is a nominal configuration of network management where a Manager
   interacts with a set of Agents.  The control flows for this are
   outlined in Figure 2.

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                    Serialized Management Control Flow

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

      In a simple network, a Manager interacts with multiple Agents.

                                 Figure 2

   In this figure, the Manager configures Agents A and B to produce EDD1
   every second in (1).  At some point in the future, upon receiving and
   configuring this message, Agents A and B then build a Report Entry
   containing EDD1 and send those reports back to the Manager in (2).

8.2.3.  Multiplexed Management

   Networks spanning multiple administrative domains may require
   multiple Managers (for example, one per domain).  When a Manager
   defines custom Reports/Variables to an Agent, that definition may be
   tagged with an Access Control List (ACL) to limit what other Managers
   will be privy to this information.  Managers in such networks should
   synchronize with those other Managers granted access to their custom
   data definitions.  When Agents generate messages, they MUST only send
   messages to Managers according to these ACLs, if present.  The
   control flows in this scenario are outlined in Figure 3.

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                    Multiplexed Management Control Flow

        +-----------+            +-------+            +-----------+
        | Manager A |            | Agent |            | Manager B |
        +-----+-----+            +---+---+            +-----+-----+
              |                      |                      |
              |---DEF(A,V1,EDD1*2)-->|<-DEF(B, 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(*,V3,EDD3*3)--->|                      | (5)
              |                      |                      |
              |---PROD(1s, V3)------>|                      | (6)
              |                      |                      |
              |                      |<----PROD(1s, V3)-----|
              |                      |                      |
              |<--------RPT(V3)------|--------RPT(V3)------>| (7)
              |<--------RPT(V1)------|                      |
              |                      |--------RPT(V2)------>|
              |<-------RPT(V1)-------|                      |
              |                      |--------RPT(V2)------>|

    Complex networks require multiple Managers interfacing with Agents.

                                 Figure 3

   In more complex networks, any Manager may choose to define custom
   Reports and Variables, and Agents may need to accept such definitions
   from multiple Managers.  Variable definitions may include an ACL that
   describes who may query and otherwise understand these definitions.
   In (1), Manager A defines V1 only for A while Manager B defines V2
   only for B.  Managers may, then, request the production of Report
   Entries containing these definitions, as shown in (2).  Agents
   produce different data for different Managers in accordance with
   configured production rules, as shown in (3).  If a Manager requests
   the production of a custom definition for which the Manager has no
   permissions, a response consistent with the configured logging policy
   on the Agent should be implemented, as shown in (4).  Alternatively,

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   as shown in (5), a Manager may define custom data with no
   restrictions allowing all other Managers to request and use this
   definition.  This allows all Managers to request the production of
   Report Entries containing this definition, shown in (6) and have all
   Managers receive this and other data going forward, as shown in (7).

8.2.4.  Data Fusion

   In some networks, Agents do not individually transmit their data to a
   Manager, preferring instead to fuse reporting data with local nodes
   prior to transmission.  This approach reduces the number and size of
   messages in the network and reduces overall transmission energy
   expenditure.  The AMA supports fusion of NM reports by co-locating
   Agents and Managers on nodes and offloading fusion activities to the
   Manager.  This process is illustrated in Figure 4.

                         Data Fusion Control Flow

   +-----------+        +-----------+      +---------+      +---------+
   | Manager A |        | Manager B |      | Agent B |      | Agent C |
   +---+-------+        +-----+-----+      +----+----+      +----+----+
       |                      |                 |                |
       |--DEF(A,V0,EDD1+AD2)->|                 |                | (1)
       |--PROD(EDD1&AD2,V0)-->|                 |                |
       |                      |                 |                |
       |                      |--PROD(1s,EDD1)->|                | (2)
       |                      |------------------PROD(1s, EDD2)->|
       |                      |                 |                |
       |                      |<---RPT(EDD1)----|                | (3)
       |                      |<------------------RPT(EDD2)------|
       |                      |                 |                |
       |<-----RPT(A,V0)-------|                 |                | (4)
       |                      |                 |                |

            Data fusion occurs amongst Managers in the network.

                                 Figure 4

   In this example, Manager A requires the production of a Variable V0,
   from node B, as shown in (1).  The Manager role understands what data
   is available from what agents in the subnetwork local to B,
   understanding that EDD1 is available locally and EDD2 is available
   remotely.  Production messages are produced in (2) and data collected
   in (3).  This allows the Manager at node B to fuse the collected
   Report Entries into V0 and return it in (4).  While a trivial
   example, the mechanism of associating fusion with the Manager
   function rather than the Agent function scales with fusion
   complexity, though it is important to reiterate that Agent and

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   Manager designations are roles, not individual software components.
   There may be a single software application running on node B
   implementing both Manager B and Agent B roles.

9.  IANA Considerations

   This protocol has no fields registered by IANA.

10.  Security Considerations

   Security within an AMA MUST exist in two layers: transport layer
   security and access control.

   Transport-layer security addresses the questions of authentication,
   integrity, and confidentiality associated with the transport of
   messages between and amongst Managers and Agents in the AMA.  This
   security is applied before any particular Actor in the system
   receives data and, therefore, is outside of the scope of this

   Finer grain application security is done via ACLs which are defined
   via configuration messages and implementation specific.

11.  Informative References

              Birrane, E. and R. Cole, "Management of Disruption-
              Tolerant Networks: A Systems Engineering Approach", 2010.

              Birrane, E., Burleigh, S., and V. Cerf, "Defining
              Tolerance: Impacts of Delay and Disruption when Managing
              Challenged Networks", 2011.

              Birrane, E. and H. Kruse, "Delay-Tolerant Network
              Management: The Definition and Exchange of Infrastructure
              Information in High Delay Environments", 2011.

              Birrane, E. and V. Ramachandran, "Delay Tolerant Network
              Management Protocol", draft-irtf-dtnrg-dtnmp-01 (work in
              progress), December 2014.

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,

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   [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,

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

   [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,

Author's Address

   Edward J. Birrane
   Johns Hopkins Applied Physics Laboratory


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