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Delay-Tolerant Networking                                     E. Birrane
Internet-Draft                  Johns Hopkins Applied Physics Laboratory
Intended status: Informational                           August 20, 2015
Expires: February 21, 2016

                  Asynchronous Management Architecture


   This document describes the motivation, desirable properties, system
   model, roles/responsibilities, and component models associated with
   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 human-in-the-loop operations centers with
   synchronous feedback in the context of administrative sessions.  In
   such a context, networks must exhibit behavior that is both
   deterministic and autonomous while maintaining compatibility with
   existing network management protocols and operational concepts.

Status of This Memo

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

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
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   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on February 21, 2016.

Copyright Notice

   Copyright (c) 2015 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of

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   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Purpose . . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.3.  Requirements Language . . . . . . . . . . . . . . . . . .   5
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   5
   3.  Motivation  . . . . . . . . . . . . . . . . . . . . . . . . .   7
     3.1.  Challenged Networks . . . . . . . . . . . . . . . . . . .   7
     3.2.  Current Management Approaches . . . . . . . . . . . . . .   8
     3.3.  Limitations of Current Approaches . . . . . . . . . . . .   9
   4.  Service Definitions . . . . . . . . . . . . . . . . . . . . .   9
     4.1.  Configuration . . . . . . . . . . . . . . . . . . . . . .   9
     4.2.  Reporting . . . . . . . . . . . . . . . . . . . . . . . .  10
     4.3.  Parameterized Control . . . . . . . . . . . . . . . . . .  11
     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.  Specific Data Identification  . . . . . . . . . . . . . .  13
     5.4.  Custom, Tactical Data Definition  . . . . . . . . . . . .  13
     5.5.  Autonomous Operation  . . . . . . . . . . . . . . . . . .  13
   6.  Roles and Responsibilities  . . . . . . . . . . . . . . . . .  13
     6.1.  Agent Responsibilities  . . . . . . . . . . . . . . . . .  14
     6.2.  Manager Responsibilities  . . . . . . . . . . . . . . . .  15
   7.  System Model  . . . . . . . . . . . . . . . . . . . . . . . .  16
     7.1.  Data Flows  . . . . . . . . . . . . . . . . . . . . . . .  16
     7.2.  Control Flow by Role  . . . . . . . . . . . . . . . . . .  17
       7.2.1.  Notation  . . . . . . . . . . . . . . . . . . . . . .  17
       7.2.2.  Serialized Management . . . . . . . . . . . . . . . .  17
       7.2.3.  Multiplexed Management  . . . . . . . . . . . . . . .  18
       7.2.4.  Data Fusion . . . . . . . . . . . . . . . . . . . . .  20
   8.  Logical Data Model  . . . . . . . . . . . . . . . . . . . . .  21
     8.1.  Data Representation . . . . . . . . . . . . . . . . . . .  21
       8.1.1.  Types . . . . . . . . . . . . . . . . . . . . . . . .  21
       8.1.2.  Classification  . . . . . . . . . . . . . . . . . . .  21
     8.2.  Data Model  . . . . . . . . . . . . . . . . . . . . . . .  22
       8.2.1.  Primitive Values, Computed Values, and Reports  . . .  23
       8.2.2.  Controls and Macros . . . . . . . . . . . . . . . . .  24
       8.2.3.  Rules . . . . . . . . . . . . . . . . . . . . . . . .  24
       8.2.4.  Operators and Literals  . . . . . . . . . . . . . . .  25

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     8.3.  Application Data Model  . . . . . . . . . . . . . . . . .  25
   9.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  26
   10. Security Considerations . . . . . . . . . . . . . . . . . . .  26
   11. Informative References  . . . . . . . . . . . . . . . . . . .  26
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  27

1.  Introduction

   This document presents an Asynchronous Management Architecture (The
   AMA) providing 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 delay drivers such as
   unavailability of network operators, administrative delays, or delays
   caused by quality-of-service prioritizations and service-level

1.1.  Purpose

   This document describes the motivation, rationale, desirable
   properties, and roles/responsibilities associated with an
   asynchronous management architecture (AMA) suitable for providing
   network management services in a challenged networking environment.
   These descriptions should be of sufficient specificity such that an
   implementing Network Management Protocol (NMP) conformant with this
   architecture will operate successfully in a challenged networking

   An AMA is necessary as the assumptions inherent to the architecture
   and design of synchronous management tools and techniques fail in
   challenged network scenarios.  Absent an asynchronous management
   approach, network operators must either adapt to scaling outages of
   common network management functionality or, more often, must invest
   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.  The ability to asynchronously manage asynchronous
   networks enables the large-scale deployment of such networks
   providing both enhanced technical capabilities and reduced deployment
   and operations costs.  This document presents six sections that,
   together, describe an AMA suitable for enterprise management of
   asynchronous networks: motivation, service definitions, desirable
   properties, roles/responsibilities, system model, and logical
   component model.  The purpose of each section is as follows.

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   o  Motivation - Synchronous management protocols operate using a
      series of implied assumptions regarding the bi-directional
      exchange of information in the context of a management session.
      Further, many such tools also pre-suppose a human-in-the-loop
      operations model.  A description of common network management
      functions and how synchronous mechanisms fail to provide these
      functions in an asynchronous network motivates and distinguishes
      this work from current management approaches.

   o  Service Definitions - A working definition of network management
      services for asynchronous networks provides the terminology,
      scope, and impact of the AMA.  Where practical, these definitions
      follow from network management definitions for synchronous

   o  Desirable Properties - desirable properties capture core
      architectural principles such that any network management protocol
      (NMP) which adheres to these properties may be considered an
      asynchronous network management protocol (AMP).  These properties
      are the basis for the system model, roles, and components that
      comprise the AMA.

   o  Roles and Responsibilities - The identification of the roles of
      logical actors in the AMA and their associated responsibilities
      provide the context for discussing how network management services
      interact in the context of a system model.

   o  System Model - The AMA system model describes significant data
      flows amongst the various defined actor roles.  These flows
      capture how the AMA system works to provide asynchronous network
      management services in accordance with defined desirable

   o  Logical Component Model - The description of the AMA is completed
      by the description of key logical components that should exist in
      any physical instantiation of an AMP.  Notably, physical
      instantiations are not required to follows, exactly, this model
      but should provide traceability to this model.

1.2.  Scope

   It is assumed that any challenged network where network management
   would be usefully applied support basic services such as naming,
   addressing, security, fragmentation, and traditional network/session
   layer functions.  Therefore, these items are not covered in this
   architectural document.

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   While likely that a challenged network will interface with a non-
   challenged network, this architecture does not address the concept of
   network management compatibility with traditional, non-challenged
   network management approaches.  Implementing NMPs conformant with
   this architecture should examine compatibility with existing
   approaches as part of supporting nodes acting as gateways between
   network types.

1.3.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in RFC 2119 [RFC2119].

2.  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  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  Asynchronous Management Protocol (AMP) - A Network Management
      Protocol (NMP) that functions as designed in the absence of
      reliable, session-based communications amongst nodes in a network.

   o  Application Data Model (ADM) - The set of predefined data
      definitions, reports, literals, operations, and controls given to
      an Actor to manage a particular application or protocol.  Actors
      support multiple ADMs, one for each application/protocol being

   o  Atomic Data - Globally unique, managed data definitions, similar
      to those defined in a Management Information Base (MIB), whose
      definition does not change based on the configuration of an Actor.
      Atomic data comprise the "lingua franca" within the AMA.  NMPs
      operate either directly on atomic data or on data derived from

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      atomic data.  Atomic data are specified in Application Data Models

   o  Computed Data - Data items that are computed dynamically by an
      Actor from some combination of Atomic Data and other Computed
      Data.  Computed data definitions are specified in both Application
      Data Models (ADMs) and tactically as part of per-network

   o  Controls - Operations that may be undertaken by an Actor to change
      the behavior, configuration, or state of an application or
      protocol managed by an NMP.  Controls are specified in Application
      Data Models (ADMs).

   o  Literals - Constant definitions and other magic numbers used in
      the evaluation of the state of Agents in the network.  Literals
      are specified in both Application Data Models (ADMs) and
      tactically as part of per-network configurations.

   o  Macros - A named, ordered collection of controls.  Macro
      definitions are specified in both Application Data Models (ADMs)
      and tactically as part of per-network configurations.

   o  Managed Item Definition (MID) - A parameterized structure used to
      uniquely identify all data and control definitions within an NMP.

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

   o  Network Management Protocol (NMP) - An application-layer protocol
      used to manage the data, controls, and other items necessary for
      configuration, monitoring, and administration of applications and
      protocols on a node in a network.  NMPs in this context do not
      manage the physical or data link layers of a networking stack.
      They may, however, assist in the configuration of software-defined

   o  Operator - The enumeration and specification of a mathematical
      function used to calculate computed data definitions and construct
      expressions to calculate spacecraft state.  Operators are
      specified in Application Data Models (ADMs).

   o  Report - A named, ordered collection of data items gathered by one
      or more Agents and provided to one or more Managers.  Reports are

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      specified in Application Data Models (ADMs) and tactically as part
      of per-network configurations.

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

3.  Motivation

   The characteristics of challenged networks, to include those networks
   challenged by administrative or policy delays, do not conform to
   several assumptions made by current network management approaches.
   These assumptions include high-rate, high-available data, round-trip
   data exchange, and operator-in-the-loop operation.  The inability of
   current approaches to provide network management services in a
   challenged network motivate 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, 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
   queueing 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 non-environmental limitations.  For
   example, networks whose operations centers are understaffed or where
   data volume and management requirements exceed the real-time
   cognitive load of operators or the associated operations console
   software support.  Also, networks where policy prevents certain data
   users from utilizing existing bandwidth also create delayed and
   disrupted environments that create administratively controlled
   periods of no communication.

   Regardless of the reason, during periods of no communications nodes
   must rely on fault-management and other autonomous mechanisms to
   ensure the safe operation of the node and its ability to usefully re-
   join the network at a later time.  In cases of sparsely-populated
   networks, there may never be a practical concept of "the connected

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   network" as most nodes may be disconnected most of the time.  In such
   environments, defining a network in terms of instantaneous
   connectivity becomes impractical or impossible.

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

   o  Links may be uni-directional.

   o  Bi-directional links may have asymmetric 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.

3.2.  Current Management Approaches

   Network management in non-challenged networks provides mechanisms for
   communicating locally-collected data from Agents to associated
   Managers, typically using a "pull" mechanism where data must be
   explicitly requested in order to be transmitted.

   A near ubiquitous method for management in non-challenged 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,
   counters, etc., 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 query-able data are defined in one or more
   Managed Information Bases (MIBs) which define the information for a
   particular data standard, protocol, device, or application.

   In challenged networks, the request/response method of data
   collection is neither efficient nor, at times, possible as it relies
   on sessions, round-trip latency, message retransmission, and ordered
   delivery.  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.  While a standard for networking,
   extending SNMP into this new domain is no more plausible than
   extending IP routing protocols into this domain.

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   The Network Configuration Protocol (NETCONF) provides device-level
   configuration capabilities [RFC6241].  so as to replace vendor-
   specific command line interface (CLI) 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.  However, NETCONF does place specific
   constraints on any underlying transport protocol: namely, 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.

3.3.  Limitations of Current Approaches

   Ultimately, 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 does 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.

   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 type of 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 local information held by an Agent as
   it relates to managed applications and protocols.  Such information
   refers to the data necessary to configure behavior in response to
   state and time changes on these devices.  The local information

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   configured through these services includes the data definitions from
   Application Data Models (ADMs), the specification of parameters
   associated with these models, and tactical data definitions defined
   by operators in the network.

   New configurations received by a node must be validated to ensure
   that they do not conflict with other configurations at the node, or
   prevent the node from effectively working with other nodes in its
   region.  In challenged networks there may not be sufficient time to
   prevent an erroneous or stale configuration from harming the flow of
   data through the network.

   Examples of configuration service behavior include the following.

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

   o  Creating a new report as a unique, ordered collection of known
      (R1 = {A, B, C}).

   o  Storing pre-defined, parameterized responses to potential future
      (IF X > 3 THEN RUN_CMD[PARM1]).

4.2.  Reporting

   Reporting services collect state information from an Agent, such as
   performance information, and send this information to one or more
   Managers.  The term "reporting" is used in place of the term
   "monitoring" as challenged networks cannot support closed-loop
   monitoring.  Reports received by an Agent provide best-effort
   information to 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).

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4.3.  Parameterized Control

   Control services provide mechanisms for an Agent to change its
   behavior using pre-defined, pre-configured responses from a Manager.
   By setting autonomous actions on Agents, Managers can "manage" the
   node asynchronously during periods of no communication.  Agents must
   understand a finite set of pre-programmed functions related to the
   protocols and applications managed on the device.  As such, controls
   comprise the basic autonomy mechanism within the AMA.

   Similar to reporting services, controls are run based on the Agent's
   notion of time and state in accordance with directives provided by
   configuration services.

   Examples of potential control service 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 control specifying
   which Managers may apply which services to which Agents may be
   necessary in networks dealing with multiple administrative entities
   or overlay networks crossing multiple administrative boundaries.
   Whitelists, blacklists, shared keys, PKI, 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 X 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.

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5.  Desirable Properties

   As discussed, realizing necessary service definitions given the
   characteristics of challenged networks cannot be performed using
   current network management approaches and operational concepts.  This
   section describes those desirable properties of an AMA that enable
   the implementation of service definitions in such networks.  These
   properties include open-loop, intelligent push, asynchronous
   mechanisms that can scale as message delivery delays scale.
   Ultimately, a useful AMA MUST be built around the following five
   design principles.

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
   both implies a control-session between entities and increases the
   overall message traffic in the network.  Challenged networks cannot
   guarantee timely roundtrip data-exchange and, in extreme cases, are
   comprised solely of uni-directional links.  Therefore, pull
   mechanisms must be avoided in favor of push mechanisms.

   Push mechanisms, in this context, refer to Agents making their own
   determinations relating 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 pre-determined schedule or in response to a pre-
   defined state on the Agent.  In this was 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.  Specific 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.  For example, SNMP-managed systems
   often approximate associative array lookups by (1) querying a list of
   known array keys, (2) making a key-index map, and (3) then querying a
   specific index into the array based on that map.  Ignoring the
   inefficiency of two pull requests, this mechanism fails when the
   Agent changes its key-index mapping between the first and second
   query.  AMPs must find a way to uniquely identify such data that does
   not rely on system configuration, perhaps through parameterization of
   the initial query.

5.4.  Custom, Tactical Data Definition

   Tactical 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 these smaller data sets is likely both tactical and
   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.  Performance data production, reconfiguration, and
   other activity must be autonomously evaluated and implemented by the
   impacted node.  Managers, rather than directing an Agent, configure
   the autonomy 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.

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

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6.1.  Agent Responsibilities

   Application Data Model (ADM) Support
           Agents MUST collect all data, execute all controls, and
           provide all reports and operations required by each ADM which
           the Agent claims to support.  Agents MUST enumerated
           supported ADMs so that Managers in a network understands what
           information is understood by that Agent.

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

   Autonomous Control
           Agents MUST determine, without Manager intervention, whether
           a configured control should be invoked.  Agents MUST
           periodically evaluate the conditions associated with
           configured controls and invoke those controls based on local
           state.  Agents MAY also invoke controls on other devices for
           which they act as proxy.

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

           Where applicable, Agents MUST verify the validity of custom
           data 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 Manager intervention, whether
           and when to populate and transmit a given data 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 report messages to a Manager, an Agent SHOULD prefer
           to send a single message containing multiple reports.

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   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/ADM Mapping
           Managers MUST understand what ADMs are supported by the
           various Agents with which they communicate.  Managers SHOULD
           NOT attempt to request, invoke, or refer to ADM information
           for ADMs unsupported by an agent.

   Data Collection
           Managers MUST receive information from Agents by
           asynchronously configuring the production of data 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 timespans and react in accordance with network

   Custom Definitions
           Managers SHOULD provide the ability to define custom data and
           report definitions.  Any defined 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, such as the SNMP.  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.

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7.  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.

7.1.  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 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 configurations from
   Managers on nodes B and C, and replies with reports 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 data reports received from Agents at nodes
   A and B and send these fused reports 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
   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.

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7.2.  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.

7.2.1.  Notation

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

   |     Term    |               Definition              |   Example   |
   |     AD#     |   Atomic data definition, from ADM.   |     AD1     |
   |             |                                       |             |
   |     CD#     |        Custom data definition.        | CD1 = AD1 + |
   |             |                                       |     CD0.    |
   |             |                                       |             |
   |  DEF([ACL], |    Define id from expression. Allow   |   DEF([*],  |
   |   ID,EXPR)  | managers in access control list (ACL) |  CD1, AD1 + |
   |             |          to request this id.          |     AD2)    |
   |             |                                       |             |
   |  PROD(P,ID) |  Produce ID according to predicate P. |   PROD(1s,  |
   |             |   P may be a time period (1s) or an   |     AD1)    |
   |             |         expression (AD1 > 10).        |             |
   |             |                                       |             |
   |   RPT(ID)   |       A report identified by ID.      |   RPT(AD1)  |

                           Table 1: Terminology

7.2.2.  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, AD1)---->|                     |(Step 1)
             |----------------------------PROD(1s, AD1)--->|
             |                       |                     |
             |                       |                     |
             |<-------RPT(AD1)-------|                     |(Step 2)
             |                       |                     |
             |                       |                     |
             |<-------RPT(AD1)-------|                     |
             |                       |                     |
             |                       |                     |
             |<-------RPT(AD1)-------|                     |
             |                       |                     |

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

                                 Figure 2

   In this figure, the Manager configures Agents A and B to produce
   atomic data AD1 every second in (Step 1).  At some point in the
   future, upon receiving and configuring this message, Agents A and B
   then build a report containing AD1 and send those reports back to the
   Manager in (Step 2).

7.2.3.  Multiplexed Management

   Networks spanning multiple administrative domains may require
   multiple Managers (for example, one per domain).  When a Manager
   defines custom reports/data 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,CD1,AD1*2)--->|<--DEF(B, CD2, AD2*2)-|(Step 1)
             |                      |                      |
             |---PROD(1s, CD1)----->|<---PROD(1s, CD2)-----|(Step 2)
             |                      |                      |
             |<-------RPT(CD1)------|                      |(Step 3)
             |                      |--------RPT(CD2)----->|
             |<-------RPT(CD1)------|                      |
             |                      |--------RPT(CD2)----->|
             |                      |                      |
             |                      |<---PROD(1s, CD1)-----|(Step 4)
             |                      |                      |
             |                      |--ERR(CD1 no perm.)-->|
             |                      |                      |
             |--DEF(*,CD3,AD3*3)--->|                      |(Step 5)
             |                      |                      |
             |---PROD(1s, CD3)----->|                      |(Step 6)
             |                      |                      |
             |                      |<---PROD(1s, CD3)-----|
             |                      |                      |
             |<-------RPT(CD3)------|--------RPT(CD3)----->|(Step 7)
             |<-------RPT(CD1)------|                      |
             |                      |--------RPT(CD2)----->|
             |<-------RPT(CD1)------|                      |
             |                      |--------RPT(CD2)----->|

    Complex networks require multiple Managers interfacing with Agents.

                                 Figure 3

   In more complex networks, Managers may choose to define custom
   reports and data definitions, and Agents may need to accept such
   definitions from multiple Managers.  Custom data definitions may
   include an ACL that describes who may query and otherwise understand
   the custom definition.  In (Step 1), Manager A defines CD1 only for A
   while Manager B defines CD2 only for B.  Managers may, then, request
   the production of reports containing these custom definitions, as
   shown in (Step 2).  Agents produce different data for different
   Managers in accordance with configured production rules, as shown in
   (Step 3).  If a Manager requests an operation, such as a production
   rule, for a custom data definition for which the Manager has no
   permissions, a response consistent with the configured logging policy

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   on the Agent should be implemented, as shown in (Step 4).
   Alternatively, as shown in (Step 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 reports containing this definition, shown in (Step 6) and have all
   Managers receive this and other data going forward, as shown in (Step

7.2.4.  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.  DTNMP 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,CD0,AD1+AD2)->|                 |                |(Step 1)
     |--PROD(AD1&AD2, CD0)->|                 |                |
     |                      |                 |                |
     |                      |--PROD(1s,AD1)-->|                |(Step 2)
     |                      |-------------------PROD(1s, AD2)->|
     |                      |                 |                |
     |                      |<---RPT(AD1)-----|                |(Step 3)
     |                      |<-------------------RPT(AD2)------|
     |                      |                 |                |
     |<-----RPT(A,CD0)------|                 |                |(Step 4)
     |                      |                 |                |

            Data fusion occurs amongst Managers in the network.

                                 Figure 4

   In this example, Manager A requires the production of a computed data
   set, CD0, from node B, as shown in (Step 1).  The manager role
   understands what data is available from what agents in the subnetwork
   local to B, understanding that AD1 is available locally and AD2 is
   available remotely.  Production messages are produced in (Step 2) and
   data collected in (Step 3).  This allows the manager at node B to
   fuse the collected data reports into CD0 and return it in (Step 4).
   While a trivial example, the mechanism of associating fusion with the

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   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.

8.  Logical Data Model

   This section enumerates the different kinds of information present in
   an asynchronously-managed network and describes how this information
   should be communicated in the context of an ADM.

8.1.  Data Representation

8.1.1.  Types

   The AMA notionally supports four basic types of information: Data,
   Controls, Literals, and Operators:

   Value   Values consist of information collected by an Agent and
           reported to Managers.  This includes definitions from an ADM,
           derived values as configured from Managers, and reports which
           are collections of data elements.

   Controls  Controls consist of actions that may be invoked on Agents
           and Managers to change behavior in response to some external
           event (such as local state changes or time).  Controls
           include application-specific functions specified as part of
           an ADM and macros which are collections of these controls.

   Literals  Literals are constant numerical values that may be used in
           the evaluation of expressions and predicates.

   Operators  Operators are those mathematical functions that operate on
           series of Data and Literals, such as addition, subtraction,
           multiplication, and division.

8.1.2.  Classification

   The AMA notionally defines three data classifications that describe
   the origins and multiplicity of data types within the system.  These
   classifications are atomic, computed, and collection.

           The Atomic classification contains those data types that are
           directly specified by an ADM and not otherwise derived from
           other identified data.  Atomic data is, therefore, not
           subject to change.  Atomic component identifiers MUST be

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           unique and SHOULD be managed by a registration authority,
           perhaps similar to the mechanisms used to assign Object
           Identifiers (OIDs).

           The Computed classification contains those data types whose
           definition is computed from some operation applied to one or
           more pieces of data.  Computed data items may be formally
           specified in an ADM (and therefore not subject to change) or
           may be defined by users/operators within a system and
           therefore subject to change in accordance with configuration
           services.  Specifically, the definition of a computed
           component MAY be dynamically defined by Managers and
           communicated to one or more Agents in a network.  The
           definition of a computed component may include other computed
           components or other atomic components.  The identifier of a
           computed component is not guaranteed to be universally unique
           but MUST be unique within the context of a particular network
           or internetwork.

           The Collection classification represents a set of
           information, including atomic data, computed data, and other

8.2.  Data Model

   Each component of the DTNMP data model can be identified as a
   combination of type and category, as illustrated in Table 2.  In this
   table type/category combinations that are unsupported are listed as
   N/A.  Specifically, DTNMP does not support user-defined controls,
   constants, or operations; any value that specifies action on an agent
   MUST be pre-configured as part of an ADM.

     |            |       Data      |  Action | Literals | Operator |
     |   Atomic   | Primitive Value | Control | Literal  | Operator |
     |            |                 |         |          |          |
     |  Computed  |  Computed Value |   Rule  |   N/A    |   N/A    |
     |            |                 |         |          |          |
     | Collection |      Report     |  Macro  |   N/A    |   N/A    |

                                  Table 2

   The eight elements of the AMA logical data model are described as

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8.2.1.  Primitive Values, Computed Values, and Reports

   Fundamental to any performance reporting function is the ability to
   measure the state of value on the Agent.  Measurement may be
   accomplished through direct sampling of hardware, query against in-
   situ data stores, or other mechanisms that provide the initial
   quantification of state.

   Primitive values serve as the "lingua franca" of the management
   system: the unit of information that cannot be otherwise created.  As
   such, this information serves as the basis for any user-defined
   (computed) values in the system.

   AMPs MAY consider the concept of the confidence of the primitive
   value as a function of time.  For example, to understand at which
   point a measurement should be considered stale and need to be re-
   measured before acting on the associated data.  For example, one
   approach to mitigate this concern is to measure values on-demand.
   Another approach is to populate a centralized data store of values
   and refresh that data store according to some pre-defined period.

   While primitives provide the full, raw set of information available
   to Managers and Agents there is a performance optimization to pre-
   computed re-used combinations of these values.  Computing new values
   as a function of measured values simplifies operator specifications
   and prevents Agent implementations from continuously re-calculating
   the same value each time it is used in a given time period.

   For example, consider a sensor node which wishes to report a
   temperature averaged over the past 10 measurements.  An Agent may
   either transmit all 10 measurements to a Manager, or calculate
   locally the average measurement and transmit the "fused" data.
   Clearly, the decision to reduce data volume is highly coupled to the
   nature of the science and the resources of the network.  For this
   reason, the ability to define custom computations per deployment is

   Periodically, or in accordance with local state changes, Agents must
   collect a series of measured values and computed values and
   communicate them back to Managers.  This ordered collection of value
   information is noted in this architecture as a "report".  In support
   of hierarchical definitions, reports may, themselves, contain other
   reports.  It would be incumbent on an AMP implementation to guard
   against circular reference in report definitions.

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8.2.2.  Controls and Macros

   Just as traditional network management approaches provide well-known
   identifiers for values, the AMA must provide a similar service for
   taking action on a node.  Whereas several low-latency, high-
   availability approaches in networks can use approaches such as remote
   procedure calls (RPCs), challenged networks cannot provide a similar
   function - Managers cannot be in the processing loop of an Agent when
   the Agent is not in communication with the Manager.

   Controls in a system are the combination of a well-known operation
   that can be taken by an Agent as well as any parameters that are
   necessary for the proper execution of that function.  For specific
   applications or protocols a control specification (as a series of
   opcodes) can be published such that any implementing AMP accepts
   these opcodes and understands that sending the opcodes to an Agent
   supporting the application or protocol will properly execute the
   associated function.  Parameters to such functions are provided in
   real-time by either Managers requesting that a control be run, pre-
   configured, or auto-populated by the Agent in-situ.

   Often, a series of controls must be executed in concert to achieve a
   particular function, especially when controls represent more
   primitive operations for a particular application/protocol.  In such
   scenarios, an ordered collection of controls can be specified as a
   "macro".  In support of the hierarchical build-up of functionality,
   macros may, themselves, contain other macros, through it would be
   incumbent on an AMP implementation to guard against excessive
   recursion or other resource-intensive nesting.

8.2.3.  Rules

   Stimulus-response autonomy systems provide a way to pre-configure
   responses to anticipated events.  Such a mapping from responses to
   events is advantageous in a challenged network for a variety of
   reasons, as listed below.

   o  Distributed Operation - The concept of pre-configuration allows
      the Agent to operate without regular contact with Managers in the
      system.  Configuration opportunities will be sporadic in any
      challenged network making bootstrapping of the system difficult,
      but this is a fundamental problem in any network scenario and any
      autonomy approach.

   o  Deterministic Behavior - Where the mapping of stimulus to response
      is stable, the behavior of the Agent to a variety of in-situ state
      also remains stable.  This stable behavior is necessary in

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      critical operational systems where the actions of a platform must
      be well understood even in the absence of an operator in the loop.

   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.  The benefit of
      engine-based approaches is that the configuration inputs to the
      engine can be flexible without incurring a set of problematic
      requirements or concerns.

   The logical unit of stimulus-response autonomy proposed in the AMA is
   a "rule" of the form:
   IF stimulus THEN response
   Where the set of such rules, when evaluated in some prioritized
   sequence, provides the full set of autonomous behavior for an Agent.
   Stimulus in such a system would either be a function of relative
   time, absolute time, or some mathematical expression comprising one
   or more values (measurement values or computed values).

   Notably, in such a system, stimuli and responses from multiple
   applications and protocols may be combined to provide an expressive

8.2.4.  Operators and Literals

   The act of computing values or evaluating the expressions that
   comprise a stimulus in a rule both require applying mathematical
   operations to data known to the management system.

   Operators in the AMA represent enumerated mathematical operations
   applied to primitive and computed data in the AMA for the purpose of
   creating new values.  Operations may be simple binary operations such
   as "A + B" or more complex functions such as sin(A) or avg(A,B,C,D).

   Literals represent pre-configured constants in the AMA, such as well-
   known mathematical numbers (e.g., PI, E), or other useful data such
   as Epoch times.  Literals also represent asserted primitive values
   used in expressions.  For example, considering the expression (A = B
   + 10), A would be a computed value, B would be either computed value
   or a primitive value, + would be an operator, and 10 would be a

8.3.  Application Data Model

   Application data models (ADMs) specify the data associated with a
   particular application/protocol.  The purpose of the ADM is to
   provide a guaranteed interface for the management of an application
   or protocol independent of the nuances of its software

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   implementation.  In this respect, the ADM is conceptually similar to
   the Managed Information Base (MIB) used by SNMP, but contains
   additional information relating to command opcodes and more
   expressive syntax for automated behavior.

   Within the AMA, an ADM MUST define all well-known items necessary to
   manage the specific application or protocol.  This includes the
   definitions of primitive values, measured values, reports, controls,
   macros, rules, literals, and operators.

9.  IANA Considerations

   At this time, 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.

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              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,

   [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

   Email: Edward.Birrane@jhuapl.edu

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