Asynchronous Management Architecture
draft-ietf-dtn-ama-03
Delay-Tolerant Networking E.J. Birrane
Internet-Draft E. Annis
Intended status: Informational S.E. Heiner
Expires: 28 April 2022 Johns Hopkins Applied Physics Laboratory
October 2021
Asynchronous Management Architecture
draft-ietf-dtn-ama-03
Abstract
This document describes a management architecture suitable for
deployment in challenged networking environments for the
configuration, monitoring, and local control of application services.
Challenged networking environments exhibit interruptions in end-to-
end connectivity and communications delays that are both long-lived
and unpredictable. Even in these challenging conditions, such
networks must provide some type of end-to-end information transport
and fault protection while also supporting configuration and
performance reporting. This management may need to operate without
human- or system-in-the-loop synchronous interactivity and without
the preservation of transport-layer sessions. In such a context,
challenged networks must exhibit behavior that is both determinable
and autonomous while maintaining as much compatibility with non-
challenged-network operational concepts as possible.
The architecture described in this document is termed the
Asynchronous Management Architecture (AMA). The AMA supported two
types of asynchronous behavior. First, the AMA does not presuppose
any synchronized transport behavior between managed and managing
devices. Second, the AMA does not support any query-response
semantics. In this way, the AMA allows for operation in extremely
challenging conditions, to include over uni-directional links and
cases where delays/disruptions would otherwise prevent operation over
traditional transport layers, such as when exceeding the Maximum
Segment Lifetime (MSL) of the Transmission Control Protocol (TCP).
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2. Requirements Language . . . . . . . . . . . . . . . . . . 5
1.3. Organization . . . . . . . . . . . . . . . . . . . . . . 5
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 6
3. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.1. Challenged Networks . . . . . . . . . . . . . . . . . . . 9
3.2. Current Approaches and Their Limitations . . . . . . . . 10
3.2.1. Simple Network Management Protocol (SNMP) . . . . . . 10
3.2.2. YANG, NETCONF, and RESTCONF . . . . . . . . . . . . . 11
3.2.3. Constrained RESTful Network Management . . . . . . . 13
4. Services Provided by an AMA . . . . . . . . . . . . . . . . . 13
4.1. Configuration . . . . . . . . . . . . . . . . . . . . . . 14
4.2. Reporting . . . . . . . . . . . . . . . . . . . . . . . . 14
4.3. Autonomous Parameterized Procedure Calls . . . . . . . . 15
4.4. Administration . . . . . . . . . . . . . . . . . . . . . 16
5. Desirable Properties of an AMA . . . . . . . . . . . . . . . 16
5.1. Intelligent Push of Information . . . . . . . . . . . . . 16
5.2. Minimize Message Size Not Node Processing . . . . . . . . 17
5.3. Absolute Data Identification . . . . . . . . . . . . . . 17
5.4. Custom Data Definition . . . . . . . . . . . . . . . . . 18
5.5. Autonomous Operation . . . . . . . . . . . . . . . . . . 18
6. AMA Roles and Responsibilities . . . . . . . . . . . . . . . 19
6.1. Agent Responsibilities . . . . . . . . . . . . . . . . . 19
6.2. Manager Responsibilities . . . . . . . . . . . . . . . . 20
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7. Logical Data Model . . . . . . . . . . . . . . . . . . . . . 21
7.1. Data Representations: Constants, Externally Defined Data,
and Variables . . . . . . . . . . . . . . . . . . . . . . 21
7.2. Data Collections: Reports and Tables . . . . . . . . . . 22
7.2.1. Report Templates and Reports . . . . . . . . . . . . 22
7.2.2. Table Templates and Tables . . . . . . . . . . . . . 23
7.3. Command Execution: Controls and Macros . . . . . . . . . 23
7.4. Autonomy: Time and State-Based Rules . . . . . . . . . . 24
7.4.1. State-Based Rule (SBR) . . . . . . . . . . . . . . . 24
7.4.2. Time-Based Rule (TBR) . . . . . . . . . . . . . . . . 25
7.5. Calculations: Expressions, Literals, and Operators . . . 25
8. System Model . . . . . . . . . . . . . . . . . . . . . . . . 26
8.1. Control and Data Flows . . . . . . . . . . . . . . . . . 26
8.2. Control Flow by Role . . . . . . . . . . . . . . . . . . 27
8.2.1. Notation . . . . . . . . . . . . . . . . . . . . . . 27
8.2.2. Serialized Management . . . . . . . . . . . . . . . . 27
8.2.3. Multiplexed Management . . . . . . . . . . . . . . . 28
8.2.4. Data Fusion . . . . . . . . . . . . . . . . . . . . . 30
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 31
10. Security Considerations . . . . . . . . . . . . . . . . . . . 31
11. Informative References . . . . . . . . . . . . . . . . . . . 31
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 33
1. Introduction
The Asynchronous Management Architecture (AMA) provides a novel
approach for the configuration, monitoring, and local control of
application services on a managed device over a challenged network.
The unique properties of a challenged network are as defined in
[RFC7228] and include cases where an end-to-end transport path may
not be feasible at any moment in time and delivery delays may 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 quality-of-service prioritizations and
service-level agreements.
Importantly, the management approach for a challenged network must be
one which remains operational in the most restrictive environments in
which such networks might be instantiated. The AMA approach should
be functional in a variety of potential management scenarios, to
include the following.
* Managed devices that are only accessible via a uni-directional
link, or via a link whose duration is shorter than a single round-
trip propagation time.
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* Links that may be significantly constrained by capacity or
reliability, but at (predictable or unpredictable) times may offer
significant throughput.
* Multi-hop challenged networks that interconnect two or more
unchallenged networks such that managed and managing devices exist
in different networks.
In these and related scenarios, managed devices need to operate with
a certain level of local autonomy because managing devices may not be
available within operationally-relevant timeframes. Managing devices
deliver instruction sets that govern the local, autonomous behavior
of the managed device. These behaviors include, but are not limited
to, collecting performance data, state, and error conditions, and
applying pre-determined responses to pre-determined events.
The AMA is a novel approach to management that can leverage
transport, network, and security solutions designed for challenged
networks, but is not bound to any single solution. The goal is
asynchronous communication between the device being managed and the
manager, at times never expecting a reply, and with knowledge that
commands and queries may be delivered much later than the initial
request.
More generally, the AMA approach is designed such that it can be
deployed in all environments in which the Delay/Disruption-Tolerant
(DTN) Bundle Protocol (BPv7) [I-D.ietf-dtn-bpbis] may be deployed.
1.1. Scope
This document describes the motivation, services, desirable
properties, roles/responsibilities, logical data model, and system
model that form the AMA. These descriptions comprise a concept of
operations for management in challenged networks with sufficient
specificity that implementations conformant with this architecture
will operate successfully in a challenged networking environment.
The AMA described herein is strictly a framework for application
management over a challenged network. The document is not a
prescriptive standardization of a physical data model or any
protocol. Instead, it serves as informative guidance to authors and
users of such models and protocols.
The AMA is independent of transport and network layers. It does not,
for example, require the use of TCP or UDP. Similarly, the AMA does
not pre-suppose the use of IPv4 or IPv6.
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The AMA is not bound to a particular security solution. It is
assumed that any network using this architecture supports those
services such as naming, addressing, integrity, confidentiality, and
authentication required to communicate AMA messages. Therefore, the
transport of these messages is outside of the scope of the AMA.
While possible that a challenged network may interface with an
unchallenged network, this document does not address the concept of
compatibility with other management approaches.
1.2. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
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 management of challenged
networks. The description of each section is as follows.
* 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.
* Motivation - This section provides an overall motivation for this
work as providing a novel and useful alternative to other network
management approaches.
* Services - This section identifies and defines the services that
an AMA will provide to network and mission operators that are
unique to operating in a challenged environment.
* Desirable Properties - This section identifies those properties of
a challenged network management system required to effectively
implement needed services. These properties guide the subsequent
definition of the system and logical models that comprise the AMA.
* Roles and Responsibilities - This section identifies roles in the
AMA and their associated responsibilities. It provides the
context for discussing how services are provided by both managers
and agents.
* Logical Data Model - This section describes the kinds of data,
procedures, autonomy, and associated hierarchal structure inherent
to the AMA.
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* System Model - This section describes data flows amongst various
defined AMA roles. These flows capture how the AMA system works
to manage devices across a challenged network.
2. Terminology
* 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.
* Agent Role (or Agent) - A role associated with a managed device,
responsible for reporting performance data, accepting/performing
controls, error handling and validation, and executing any
autonomous behaviors. AMA Agents exchange information with AMA
Managers operating either on the same device or on a remote
managing device.
* Asynchronous Management - Management that does not depend on
stateful connections or real time delivery of management messages.
Allows for delivery of management messages and instruction sets
for autonomous behavior that governs the expected actions, rules
associated with those actions, and expected reporting procedures.
Asynchronous management does not depend on underlying transport or
network protocols for reliability or addressing of source and
destination.
* Asynchronous Management Model (AMM) - data types and data
structures needed to manage applications in asynchronous networks.
* Externally Defined Data (EDD) - Information made available to an
AMA Agent by a managed device, but not computed directly by the
AMA Agent itself.
* Variables (VARs) - Typed information that is computed by an AMA
Agent, typically as a function of EDD values and/or other
variables.
* 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.
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* Controls (CTRLs) - Procedures run by an AMA Actor to change the
behavior, configuration, or state of an application or protocol
being asynchronously managed. Controls may also be used to
request data from an agent and define the rules associated with
generation and delivery.
* Literals (LITs) - A literal represents a typed 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.
* Macros (MACROs) - A named, ordered collection of Controls and/or
other Macros.
* Manager Role (or Manager) - A role associated with a managing
device responsible for configuring the behavior of, and eventually
receiving information from, AMA Agents. AMA Managers interact
with one or more AMA Agents located on the same device and/or on
remote devices in the network.
* Operator (OP) - The enumeration and specification of a
mathematical function used to calculate variable values and
construct expressions to evaluate AMA Agent state.
* Report (RPT) - A typed, ordered collection of data values gathered
by one or more AMA Agents and provided to one or more AMA
Managers. Reports only contain typed data values and the identity
of the Report Template (RPTT) to which they conform.
* 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 an AMA Manager and
communicated to one or more AMA Agents.
* Rule - A unit of autonomous specification that provides a
stimulus-response relationship between time or state on an AMA
Agent and the actions or operations to be run as a result of that
time or state. A rule might trigger updating a variable,
populating a report/table, executing a control, or initiating the
transmission of a report/table.
* State-Based Rule (SBR) - A state-based rule is any rule in which
the rule stimulus is triggered by the calculable internal state of
data model associated with the AMA Agent.
* Synchronous Management - Management that assumes messages will be
delivered and acted upon in real or near-real-time. Synchronous
management often involves immediate replies of acknowledgment or
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error status. Synchronous management is often bound to underlying
transport protocols and network protocols to ensure reliability or
source and sender identification.
* 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. Tables only contain typed data values and the identity of
the Table Template (TBLT) to which they conform.
* 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).
* Time-Based Rule (TBR) - A time-based rule is a specialization, and
simplification, of a state-based rule in which the rule stimulus
is triggered by the relative time as it is known on the Agent as a
function of either matched value or frequency.
3. Motivation
Early work into the rationale and motivation for specialized
management for challenged networks was captured in [BIRRANE1],
[BIRRANE2], and [BIRRANE3]. Some of the properties and feasibility
of such a management system were adopted from prototyping work done
in accordance with the DTN Research Group within the IRTF as
documented in [I-D.irtf-dtnrg-dtnmp].
The unique nature of challenged networks requires new network
capabilities to deliver expected network functions. For example, the
unique nature of DTNs required the development of the Bundle Protocol
for transport functions and the Bundle Protocol Security Protocol
(BPSec) is required to secure bundles in certain types of DTNs.
Similarly, new management capabilities are needed to implement
management in challenged environments, such as those defined as DTNs.
The AMA provides a method of configuring AMA Agents with local,
autonomous management functions, such as rules-based execution of
procedures and generation of reports, to achieve expected behavior
when managed devices exist over a challenged network. It further
allows for dynamic instantiation and population of Variables and
reports through local operations defined by the manager, as well as
custom formatting of tables and reports to be sent back. This gives
the AMA significant flexibility to operate over challenged networks,
both providing new degrees of freedom over existing configuration
based data models used in synchronous networks and allowing for more
concise formatting over constrained networks. This architecture
makes very few assumptions on the nature of the network and allow for
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continuous operation through periods of connectivity and lack of
connectivity. The AMA deviates from synchronous management
approaches because it never requires periods of bi-directional
connectivity, and provides the manager flexibility to describe agent
behavior that was unpredicted at the time of the data model creation.
To understand the unique motivations for the architecture, this
section discusses motivating characteristics of challenged networks,
current network management approaches, and how they might behave in a
challenged environment.
3.1. Challenged Networks
A challenged network is one that "has serious trouble maintaining
what an application would today expect of the end-to-end IP model"
([RFC7228]). This includes cases where there is never simultaneous
end-to-end connectivity, when such connectivity is interrupted at
planned or unplanned intervals, or when delays exceed those that
could be accommodated by IP-based transport. Links in such networks
are often unavailable due to attenuations, propagation delays,
mobility, occultation, and other limitations imposed by energy and
mass considerations.
Challenged networks exhibit the following properties that impact the
way in which the function of network management is considered.
* No end-to-end path is guaranteed to exist at any given time
between any two nodes.
* Round-trip communications between any two nodes within any given
time window may be impossible.
* Latencies on the order of seconds, hours, or days must be
tolerated.
* Links may be uni-directional.
* Bi-directional links may have asymmetric data rates.
One way in which constrained networks differ from challenged networks
is the way in which the topology and, otherwise, roles and
responsibilities of the network may evolve over time. From the time
at which data is generated on a source node to the time at which the
data is received at a destination node, the topology of the network
may have changed. In certain circumstances, the physical node
receiving messages for a given node identifier may also have changed.
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When this topological change impacts the transport of messages, then
transports must wait for the incremental connectivity necessary to
advance messages along their expected route. Therefore, these
networks cannot guarantee that there exist timely data exchange
between managing and managed devices. For example, the Bundle
Protocol transport protocol for use in DTNs implements this type of
store-and-forward operation.
When topological change impacts the semantic roles and
responsibilities of nodes in the network, then local configuration
and autonomy at nodes must be present to determine time-variant
changes. For example, the BPSec protocol does not encode security
destinations and, instead, requires nodes in a network to identify as
verifiers or acceptors when receiving secured messages.
When applied to network management, the semantic roles of Agent and
Manager may also change with the changing topology of the network.
Individual nodes must implement desirable behavior without reliance
on a single oracle of configuration or other coordinating function
such as an operator-in-the-loop. This implies that there MUST NOT be
a defined relationship between a particular manager and agent in a
network.
3.2. Current Approaches and Their Limitations
Network management solutions have been prevalent for many years in
both local-area and wide-area networks. These range from the
simplistic ability to configure settings of operational devices or
report on state and operational conditions; to the more more complex
modeling of an entire managed device setting, state, and behavior,
pushing and receiving large sets of configuration data between the
manager and the agent. Autonomy has more recently been applied to
network management but is focused more on well resourced,
unchallenged networks where devices self-configure, self-heal, and
self-optimize with other nodes within their vicinity. This section
describes some of the well known standardized protocols for network
management as well as various proposed solutions and aims to
differentiate their purpose with the needs of challenged network
management solutions.
3.2.1. Simple Network Management Protocol (SNMP)
Historically, network management tools in unchallenged networks
provide mechanisms for communicating locally-collected data from
devices to operators and managing applications, typically using a
"pull" mechanism where data must be explicitly requested by a Manager
in order to be transmitted by an Agent. A legacy method for
management in unchallenged networks today is the Simple Network
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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. Complex management
can be achieved but only through craftful orchestration using a
series of real-time manager generated query and response logic not
possible in challenged networks. The SNMP trap model provides some
Agent-side processing, however because the processing has very low
fidelity and traps are typically "fire and forget." Adaptive
modifications to SNMP to support challenged networks and more complex
application-level management, 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.
3.2.2. YANG, NETCONF, and RESTCONF
Yet Another Next Generation (YANG) [RFC6020] is a data modeling
language used to model configuration and state data of managed
devices and applications. The YANG model defines a schema for
organizing and accessing a device's configuration or operational
information. Once a model is developed, it is loaded to both the
client (manager) and server (agent) and serves as a contract between
the two. A YANG model can be complex, describing many containers of
managed elements, each with many configuration or operational state
data nodes. It can further define lists of like elements. YANG
allows for the definition of parameterized Remote Procedure Calls
(RPCs) to be executed on managed nodes as well as the definition of
asynchronous notifications within the model.
YANG by itself serves no purpose other than to organize data and
describe the allowed configuration parameters on the managed device.
The Network Configuration Protocol (NETCONF) [RFC6241] and the
RESTCONF protocol [RFC8040] provide the mechanisms to install,
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manipulate, and delete the configuration of network devices, using
the YANG modules. NETCONF is a stateful, XML-based protocol that
provides the RPC syntax to retrieve, edit, copy, or delete any data
nodes or exposed functionality on the server. NETCONF connections
are required to provide authentication, data integrity,
confidentiality, and replay protection through secure transport
protocols such as SSH or TLS. RESTCONF is a stateless RESTful
protocol based on HTTP that uses JSON encoding to GET, POST, PUT,
PATCH, or DELETE data nodes within the YANG modules similar to
NETCONF. RESTCONF, while stateless, still requires secure transport
such as TLS. Both NETCONF and RESTCONF place no specific functional
requirements or constraints on the capabilities of the server, which
makes it a very flexible tool for configuring a homogeneous network
of devices, however they are limiting in challenged networks due to
their requirements of underlying transport and dependence on the YANG
data models.
NETCONF places specific constraints on any underlying transport
protocol: a long-lived, reliable, low-latency sequenced data delivery
session. No data is transferred without first establishing this bi-
directional NETCONF session. RESTCONF relaxes this constraint
however is limited to requesting or configuring individual data
elements or entire containers within the YANG data model. It is
therefore quite verbose and limited by the structure previously
defined in the YANG module and any autonomous behavior depends on
client slide orchestration similar to SNMP.
As previously noted, YANG allows for the definition of RPCs within
the model and notification elements for asynchronous messaging. The
RPCs provide both the definition of input and output parameters
however are strictly allowed in NETCONF and RESTCONF to be sent as
sequential procedures. Even if multiple procedures are sent, the
server is required to execute them and reply in the order they were
received. There is also no flexibility for the state-based execution
of those procedures on the server. The RPCs are executed as soon as
they are received, ultimately limiting the degrees of autonomy of the
server. YANG notifications are quite promising for asynchronous
network management, defined as both subscriptions to YANG
notifications [RFC8639] and YANG PUSH notifications [RFC8641].
Notification containers must first be defined within the YANG module
declaring the containers or data nodes of interest. The events can
be filtered according to XPATH filtering defined in [RFC8639]
Section 6, however generation of events are streamed and generally
limited to the external changing state of a data node. YANG PUSH
allows for both periodic and on-change event notification but
supports no rules-based triggering. While the YANG data model offers
many great features, the features today are simply limiting for the
autonomous behavior required by challenged network management.
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YANG is additionally limiting for challenged networks because of its
non-hierarchal schema. While the YANG model flexibility is great for
the management of nodes and applications of any type in an
unchallenged network, it becomes a burden in challenged networks
where concise encoding is necessary. All the data nodes within a
YANG model are referenced by verbose string based path of the module,
sub-module, container, and any data nodes such as lists, leaf-lists,
or leafs. Recent efforts are underway which allow for CBOR encoding
of YANG models [I-D.ietf-core-yang-cbor] and addressing of data nodes
through integer value YANG Schema Item iDentifiers (SIDs)
[I-D.ietf-core-sid], however these lack any formal hierarchal
structure. All mapping of SIDs to YANG modules and data nodes is
preformed manually which limits the portability of models and further
increases the size of any encoding scheme.
3.2.3. Constrained RESTful Network Management
Due to the advent and ubiquity of the Internet of Things (IoT), the
Constrained Application Protocol (CoAP) [RFC7252] has been recently
developed for communicating with nodes and applications in
constrained networks. CoAP is merely the messaging framework
designed to limit message size and fragmentation, operating over IP
networks. Because constrained networks could experience interruption
similar to those in DTNs, the protocol provides for application layer
store-and-forward as well as proxy delivery of messages, but is bound
to UDP transport. An approach to network management has been
authored that uses CoAP for transport and YANG as the data model, and
is defined as CORECONF [I-D.ietf-core-comi]. This proposed protocol
makes use of the YANG to CBOR encoding including the use of SIDs to
limit message size, however is currently bound to UDP/IP transport of
CoAP and further defines security requirements including DTLS or
OSCORE. This explicit binding to transport and security protocols is
limiting when applied to novel DTN approaches designed for challenged
networks.
4. Services Provided by an AMA
This section identifies the services that an AMA would provide for
management of challenged network resources. These services include
configuration, reporting, parameterized control, and administration.
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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
network.
Examples of configuration service behavior include the following.
* Creating a new datum as a function of other well-known data:
C = A + B.
* Creating a new report as a unique, ordered collection of known
data:
RPT = {A, B, C}.
* Storing predefined, parameterized responses to potential future
conditions:
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.
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Examples of reporting service behavior include the following.
* Generate Report R1 every hour (time-based production).
* 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 affect 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 internal
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.
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.
* Updating local routing information based on instantaneous link
analysis.
* Managing storage on the device to enforce quotas.
* Applying or modifying local security policy.
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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.
* Agent A1 only Sends reports for Protocol P1 to Manager M1.
* Agent A2 only accepts a configurations for Application Y from
Managers M2 and M3.
* 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 such messages.
5. Desirable Properties of an AMA
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 round-trip 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
round-trip data exchange. Therefore, pull mechanisms must be avoided
in favor of push mechanisms.
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Push mechanisms, in this context, refer to the ability of Agents to
leverage rule-based criteria to determine when and what information
should be sent to managers. This could be based solely off logic
applied to existing VARs or EDDs, or based off operations applied to
data elements. 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. An Asynchronous Management Protocol (AMP) should minimize
PDUs whenever practical, to include packing and unpacking binary
data, variable-length fields, and pre-configured data definitions.
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.
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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. These new defined data elements could be
calculated and used both as parameters for local stimulus-response
rules-based criteria or simply serve to populate custom reports and
tables. 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.
Aggregation of controls and custom formatting of reports and tables
are is equally important. Custom reporting provides the flexibility
allowing the manager to define the desired format of all information
to be sent over the challenged network from the agents, serving to
both save link capacity and increase the value of returned
information. Aggregation of controls allows a manager to specify a
set of controls to execute, specifying both the order and criteria of
execution. This aggregate set of controls can be sent as a single
command rather than a series of sequential operands. In this case it
is additionally possible to use outputs of one command to serve as an
input to the next at the agent.
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
benefits.
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* 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.
* 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.
* 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 provide configurable behavior without incurring these
types of concerns associated with mobile code.
6. AMA Roles and Responsibilities
By definition, Agents reside on managed devices and Managers reside
on managing devices. There is however no pre-supposed architecture
that connects managers and agents and therefore a single device could
assume both roles. This section describes the responsibilities
associated with each role and how these roles participate in network
management.
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 manages. 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.
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Autonomous Control
Agents MUST determine, as previously prescribed by a manager,
whether a procedure should be invoked.
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.
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
Managers should provide the ability to define custom data
definitions. Any custom definitions MUST be transmitted to
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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
Variables
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 typed, named
values that cannot be modified once they have been defined.
Data 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 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
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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
structure.
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.
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.
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Unlike tables, reports do not exploit assumptions on the underlying
structure of their data. Therefore, unlike tables, operators can
define new reports at any time as part of the runtime configuration
of the network.
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 syntactic 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
macros.
A Control (CTRL) represents a parameterized, predefined procedure
that can be run on an Agent. While conceptually similar to a "remote
procedure call", CTRLs differ in that they do not provide numeric
return codes. The concept of a return code when running a procedure
implies a synchronous relationship between the caller of the
procedure and the procedure being called, which is disallowed in an
asynchronous management system. Instead, CTRLs may create reports
which describe the status and other summarizations of their
operation, and these reports may be sent to the Manager(s) calling
the CTRL.
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Parameters can be provided when running a command from a Manager,
pre-configured as part of a response to a time-based or state-based
rule 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
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-affecting components.
Often, a series of controls must be executed in sequence 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
implementation.
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 be activated based on Agent internal 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 may construct their stimuli from the full set of values known
to the network management system. Similarly, responses may be
constructed from the full set of controls and macros that can be run
on the Agent. By allowing rules to evaluate the variety of all known
data and run the variety of all known controls, multiple applications
can be monitored and managed by one (or few) Agent instances.
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:
IF (((current_time - base_time) % 24_hours) == 0) THEN ... 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 to 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" - its
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,
addition of integers may be defined separately from addition of real
numbers.
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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. 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
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necessarily different 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([*], |
| ID,EXPR) | managers in access control list | V1, EDD1 |
| | (ACL) to request this ID. | + 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 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.
Serialized Management Control Flow
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+----------+ +---------+ +---------+
| Manager | | Agent A | | Agent B |
+----+-----+ +----+----+ +----+----+
| | |
|-----PROD(1s, EDD1)--->| | (1)
|----------------------------PROD(1s, EDD1)-->|
| | |
| | |
|<-------RPT(EDD1)------| | (2)
|<----------------------------RPT(EDD1)-------|
| | |
| | |
|<-------RPT(EDD1)------| |
|<----------------------------RPT(EDD1)-------|
| | |
| | |
|<-------RPT(EDD1)------| |
|<----------------------------RPT(EDD1)-------|
| | |
Figure 2
In a simple network, a Manager interacts with multiple Agents.
In this figure, the Manager configures Agents A and B to produce EDD1
every second in (1). 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). This behavior then repeats
this action every 1s without requiring other inputs from the Manager.
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.
Multiplexed Management Control Flow
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+-----------+ +-------+ +-----------+
| 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(V3)-------|--------RPT(V3)------>|
|<-------RPT(V1)-------| |
| |--------RPT(V2)------>|
Figure 3
Complex networks require multiple Managers interfacing with Agents.
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,
as shown in (5), a Manager may define custom data with no access
restrictions, allowing all other Managers to request and use this
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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
Data fusion reduces the number and size of messages in the network
which can lead to more efficient utilization of networking resources.
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+EDD2)->| | | (1)
|-PROD(EDD1&EDD2,V0)-->| | |
| | | |
| |--PROD(1s,EDD1)->| | (2)
| |------------------PROD(1s, EDD2)->|
| | | |
| |<---RPT(EDD1)----| | (3)
| |<------------------RPT(EDD2)------|
| | | |
|<-----RPT(A,V0)-------| | | (4)
| | | |
Figure 4
Data fusion occurs amongst Managers in the network.
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
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.
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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
document.
Finer grain application security is done via ACLs which are defined
via configuration messages and implementation specific.
11. Informative References
[BIRRANE1] Birrane, E.B. and R.C. Cole, "Management of Disruption-
Tolerant Networks: A Systems Engineering Approach", 2010.
[BIRRANE2] Birrane, E.B., Burleigh, S.B., and V.C. Cerf, "Defining
Tolerance: Impacts of Delay and Disruption when Managing
Challenged Networks", 2011.
[BIRRANE3] Birrane, E.B. and H.K. Kruse, "Delay-Tolerant Network
Management: The Definition and Exchange of Infrastructure
Information in High Delay Environments", 2011.
[I-D.ietf-core-comi]
Veillette, M., Stok, P. V. D., Pelov, A., Bierman, A., and
I. Petrov, "CoAP Management Interface (CORECONF)", Work in
Progress, Internet-Draft, draft-ietf-core-comi-11, 17
January 2021, <https://datatracker.ietf.org/doc/html/
draft-ietf-core-comi-11>.
[I-D.ietf-core-sid]
Veillette, M., Pelov, A., Petrov, I., and C. Bormann,
"YANG Schema Item iDentifier (YANG SID)", Work in
Progress, Internet-Draft, draft-ietf-core-sid-16, 24 June
2021, <https://datatracker.ietf.org/doc/html/draft-ietf-
core-sid-16>.
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[I-D.ietf-core-yang-cbor]
Veillette, M., Petrov, I., Pelov, A., and C. Bormann,
"CBOR Encoding of Data Modeled with YANG", Work in
Progress, Internet-Draft, draft-ietf-core-yang-cbor-16, 24
June 2021, <https://datatracker.ietf.org/doc/html/draft-
ietf-core-yang-cbor-16>.
[I-D.ietf-dtn-bpbis]
Burleigh, S., Fall, K., and E. J. Birrane, "Bundle
Protocol Version 7", Work in Progress, Internet-Draft,
draft-ietf-dtn-bpbis-31, 25 January 2021,
<https://datatracker.ietf.org/doc/html/draft-ietf-dtn-
bpbis-31>.
[I-D.irtf-dtnrg-dtnmp]
Birrane, E. J. and V. Ramachandran, "Delay Tolerant
Network Management Protocol", Work in Progress, Internet-
Draft, draft-irtf-dtnrg-dtnmp-01, 31 December 2014,
<https://datatracker.ietf.org/doc/html/draft-irtf-dtnrg-
dtnmp-01>.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[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,
<https://www.rfc-editor.org/info/rfc3416>.
[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, <https://www.rfc-editor.org/info/rfc4838>.
[RFC6020] Bjorklund, M., Ed., "YANG - A Data Modeling Language for
the Network Configuration Protocol (NETCONF)", RFC 6020,
DOI 10.17487/RFC6020, October 2010,
<https://www.rfc-editor.org/info/rfc6020>.
[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,
<https://www.rfc-editor.org/info/rfc6241>.
Birrane, et al. Expires 28 April 2022 [Page 32]
Internet-Draft AMA October 2021
[RFC7228] Bormann, C., Ersue, M., and A. Keranen, "Terminology for
Constrained-Node Networks", RFC 7228,
DOI 10.17487/RFC7228, May 2014,
<https://www.rfc-editor.org/info/rfc7228>.
[RFC7252] Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
Application Protocol (CoAP)", RFC 7252,
DOI 10.17487/RFC7252, June 2014,
<https://www.rfc-editor.org/info/rfc7252>.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
<https://www.rfc-editor.org/info/rfc8040>.
[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,
<https://www.rfc-editor.org/info/rfc8639>.
[RFC8641] Clemm, A. and E. Voit, "Subscription to YANG Notifications
for Datastore Updates", RFC 8641, DOI 10.17487/RFC8641,
September 2019, <https://www.rfc-editor.org/info/rfc8641>.
Authors' Addresses
Edward J. Birrane
Johns Hopkins Applied Physics Laboratory
Email: Edward.Birrane@jhuapl.edu
Emery Annis
Johns Hopkins Applied Physics Laboratory
Email: Emery.Annis@jhuapl.edu
Sarah E. Heiner
Johns Hopkins Applied Physics Laboratory
Email: Sarah.Heiner@jhuapl.edu
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