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Delay-Tolerant Networking                                     E. Birrane
Internet-Draft                  Johns Hopkins Applied Physics Laboratory
Intended status: Informational                          October 30, 2016
Expires: May 3, 2017

                  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
   determinable 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
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   This Internet-Draft will expire on May 3, 2017.

Copyright Notice

   Copyright (c) 2016 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
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Purpose . . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.3.  Requirements Language . . . . . . . . . . . . . . . . . .   4
     1.4.  ORganization  . . . . . . . . . . . . . . . . . . . . . .   4
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   5
   3.  Motivation  . . . . . . . . . . . . . . . . . . . . . . . . .   6
     3.1.  Challenged Networks . . . . . . . . . . . . . . . . . . .   7
     3.2.  Current Management Approaches . . . . . . . . . . . . . .   8
     3.3.  Limitations of Current Approaches . . . . . . . . . . . .   8
   4.  Service Definitions . . . . . . . . . . . . . . . . . . . . .   9
     4.1.  Configuration . . . . . . . . . . . . . . . . . . . . . .   9
     4.2.  Reporting . . . . . . . . . . . . . . . . . . . . . . . .  10
     4.3.  Autonomous Parameterized Control  . . . . . . . . . . . .  10
     4.4.  Administration  . . . . . . . . . . . . . . . . . . . . .  11
   5.  Desirable Properties  . . . . . . . . . . . . . . . . . . . .  11
     5.1.  Intelligent Push of Information . . . . . . . . . . . . .  12
     5.2.  Minimize Message Size Not Node Processing . . . . . . . .  12
     5.3.  Absolute Data Identification  . . . . . . . . . . . . . .  12
     5.4.  Custom Data Definition  . . . . . . . . . . . . . . . . .  13
     5.5.  Autonomous Operation  . . . . . . . . . . . . . . . . . .  13
   6.  Roles and Responsibilities  . . . . . . . . . . . . . . . . .  13
     6.1.  Agent Responsibilities  . . . . . . . . . . . . . . . . .  13
     6.2.  Manager Responsibilities  . . . . . . . . . . . . . . . .  15
   7.  System Model  . . . . . . . . . . . . . . . . . . . . . . . .  15
     7.1.  Control and Data Flows  . . . . . . . . . . . . . . . . .  16
     7.2.  Control Flow by Role  . . . . . . . . . . . . . . . . . .  16
       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 Decomposition  . . . . . . . . . . . . . . . . . . .  21
       8.1.1.  Groups  . . . . . . . . . . . . . . . . . . . . . . .  21
       8.1.2.  Levels  . . . . . . . . . . . . . . . . . . . . . . .  21
     8.2.  Data Model  . . . . . . . . . . . . . . . . . . . . . . .  22
       8.2.1.  EDDs, VARs, and Reporting . . . . . . . . . . . . . .  23
       8.2.2.  Controls and Macros . . . . . . . . . . . . . . . . .  24
       8.2.3.  Rules . . . . . . . . . . . . . . . . . . . . . . . .  24

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       8.2.4.  Operators and Literals  . . . . . . . . . . . . . . .  25
     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 (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 factors such as unavailability
   of network operators, administrative delays, or delays caused by
   quality-of-service prioritizations and service-level agreements.

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 that an
   implementing Asynchronous Management Protocol (AMP) in conformance
   with this architecture will operate successfully in a challenged
   networking environment.

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

1.2.  Scope

   It is assumed that any challenged network where network management
   would be usefully applied supports basic services (where necessary)
   such as naming, addressing, integrity, confidentiality,

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   authentication, fragmentation, and traditional network/session layer
   functions.  Therefore, these items are outside of the scope of the
   AMA and not covered in this document.

   While likely that a challenged network will eventually interface with
   an unchallenged network, this document does not address the concept
   of network management compatibility with synchronous approaches.  An
   AMP in conformance 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 [RFC2119].

1.4.  ORganization

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

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

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

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

   o  Roles and Responsibilities - This section identifies the roles of
      logical Actors in the AMA and their associated responsibilities.
      It provides the terminology and context for discussing how network
      management services interact.

   o  System Model - This section describes data flows amongst various
      defined Actor roles.  These flows capture how the AMA system works

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      to provide asynchronous network management services in accordance
      with defined desirable properties.

   o  Logical Component Model - This section describes those logical
      functions that must exist in any instantiation of an AMP.

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) - 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 challenged 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  Externally Defined Data (EDD) - Information made available to an
      Agent by a managed device, but not computed directly by the Agent.
      EDD definitions form the "lingua franca" for data within the AMA
      and are defined by ADMs.

   o  Variable (VAR) - Information that is computed by an Agent,
      typically as a function of EDDs and/or other Variables.  A VAR is
      a strongly-typed value.  When a VAR is specified in an ADM, its
      type and default value are immutable.  When a VAR is defined
      outside of an ADM, the type and default value may be changed.  If
      an ADM wishes to define an item whose type and value are both
      immutable, that is no longer considered a Variable and should be
      represented as a Literal.

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   o  Controls (CTRLs) - Operations that may be undertaken by an Actor
      to change the behavior, configuration, or state of an application
      or protocol managed by an AMP.  Similar to Externally Defined
      Data, Controls are defined solely in ADMs and their definition is

   o  Literals (LIT) - Constants, enumerations, and other immutable

   o  Macros - A named, ordered collection of Controls.  When a Macro is
      defined in an ADM, that definition is immutable.  When a Macro is
      defined outside of an ADM, that definition may be changed.

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

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

   o  Report Entry (RPTE) - A named, typed, ordered collection of data
      values gathered by one or more Agents and provided to one or more
      Managers.  Report entries populate report templates with values.

   o  Report Template (RPTT) - An ordered collection of data
      identifiers.  When defined in an ADM the report template
      definition is immutable.  When defined outside of an ADM, the
      template definition may change.

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

3.  Motivation

   Challenged networks, to include networks challenged by administrative
   or policy delays, cannot guarantee capabilities required to enable
   synchronous management techniques.  These capabilities include high-
   rate, highly-available data, round-trip data exchange, and operators
   "in-the-loop".  The inability of current approaches to provide
   network management services in a challenged network motivates the
   need for a new network management architecture focused on
   asynchronous, open-loop, autonomous control of network components.

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3.1.  Challenged Networks

   A growing variety of link-challenged networks support packetization
   to increase data communications reliability without otherwise
   guaranteeing a simultaneous end-to-end path.  Examples of such
   networks include Mobile Ad-Hoc Networks (MANets), Vehicular Ad-Hoc
   Networks (VANets), Space-Terrestrial Internetworks (STINTs), and
   heterogeneous networking overlays.  Links in such networks are often
   unavailable due to attenuations, propagation delays, occultation, and
   other limitations imposed by energy and mass considerations.  Data
   communications in such networks rely on store-and-forward and other
   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 restricts user access
   to existing bandwidth creates situations functionally similar to link
   disruption and delay.

   Independent of the reason, when a node experiences an inability to
   communicate it must rely on autonomous mechanisms to ensure its safe
   operation and ability to usefully re-join the network at a later
   time.  In cases of sparsely-populated networks, there may never be a
   practical concept of "the connected 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

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

   o  Links may be uni-directional.

   o  Bi-directional links may have asymmetric data rates.

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

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

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3.2.  Current Management Approaches

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

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

   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.

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

   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.

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   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 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 Agent information relating to
   managed applications and protocols.  This information may be
   configured from ADMs, the specification of parameters associated with
   these models, and as 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.  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.

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

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

   o  Storing pre-defined, parameterized responses to potential future

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      IF (X > 3) THEN RUN CMD(PARM).

4.2.  Reporting

   Reporting services populate pre-defined Report Templates with values
   collected or computed by an Agent.  The resultant Report Entries 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.  Report Entries 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 Report Entries based
   on its own local time and state information.  Agents should produce
   Report Entries of varying fidelity and with varying frequency based
   on thresholds and other information set as part of configuration

   Examples of reporting service behavior include the following.

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

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

4.3.  Autonomous Parameterized Control

   Controls represent a function that can be run by an Agent to affect
   its behavior or otherwise change its internal state.  In this
   context, a Control may refer to a single function or an ordered set
   of functions run in sequence (e.g., a macro).  The set of Controls
   understood by an Agent define the functions available to affect the
   behavior of applications and protocols managed by the Agent.

   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 Control
   should be run must be made locally and autonomously by the Agent.
   Two types of automation triggers are identified in the AMA: triggers
   based on the general state of the Agent and, more specifically,
   triggers based on an Agent's notion of time.  As such, the autonomous
   execution of Controls 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 Control to be executed.

   The autonomous nature of Control execution by an Agent implies that
   the full suite of information necessary to run a Control may not be
   known by a Manager in advance of running the Control on an Agent.  To
   address this situation, Controls in the AMA MUST support a

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   parmeterization mechanism 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 control provides 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 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, key-based infrastructures, or other schemes
   may be used for this purpose.

   Examples of administration service behavior include the following.

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

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

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

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

5.  Desirable Properties

   This section describes those design properties that are desireable
   when defining an architecture that must operate across challenged
   links in a network.  These properties ensure that network management

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   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
   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 way information is "pushed" from
   Agents to Managers and the push is "intelligent" because it is based
   on some internal evaluation performed by the Agent.

5.2.  Minimize Message Size Not Node Processing

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

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.

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   Consider the following SNMP 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 matched K1 and infer the index of K1
   from the returned key list, and (3) query the discovered index on the
   agent to retrieve the desired data.

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

5.4.  Custom Data Definition

   Custom definition of new data from existing data (such as through
   data fusion, averaging, sampling, or other mechanisms) provides the
   ability to communicate desired information in as compact a form as
   possible.  Specifically, an Agent should not be required to transmit
   a large data set for a Manager that only wishes to calculate a
   smaller, inferred data set.  The Agent should calculate the smaller
   data set on its own and transmit that instead.  Since the
   identification of custom data sets is likely to occur in the context
   of a specific network deployment, AMPs must provide a mechanism for
   their definition.

5.5.  Autonomous Operation

   AMA network functions must be achievable using only knowledge local
   to the Agent.  Rather than directly controlling an Agent, a Manager
   configures 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

6.1.  Agent Responsibilities

   Application Data Model (ADM) Support
           Agents MUST collect all data, execute all Controls, populate
           all Report Templates and run operations required by each ADM
           which the Agent claims to support.  Agents MUST report

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           supported ADMs 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 Externally Defined 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 Variables,
           Report Templates, Macros and other information 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 Entry targeted to one or more Managers in the

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

   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.

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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
           definitions.  Any custom definitions MUST be transmitted to
           appropriate Agents and these definitions MUST be remembered
           to interpret the reporting of these custom values from Agents
           in the future.

   Data Translation
           Managers should provide some interface to other network
           management protocols, 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.

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.

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7.1.  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
   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.

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.

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7.2.1.  Notation

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

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

                           Table 1: Terminology

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, EDD1)--->|                     | (1)
              |----------------------------PROD(1s, EDD1)-->|
              |                       |                     |
              |                       |                     |
              |<-------RPT(EDD1)------|                     | (2)
              |                       |                     |
              |                       |                     |
              |<-------RPT(EDD1)------|                     |
              |                       |                     |
              |                       |                     |
              |<-------RPT(EDD1)------|                     |
              |                       |                     |

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

                                 Figure 2

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

7.2.3.  Multiplexed Management

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

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                    Multiplexed Management Control Flow

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

    Complex networks require multiple Managers interfacing with Agents.

                                 Figure 3

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

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

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.  The AMA supports fusion of NM reports by co-locating
   Agents and Managers on nodes and offloading fusion activities to the
   Manager.  This process is illustrated in Figure 4.

                         Data Fusion Control Flow

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

            Data fusion occurs amongst Managers in the network.

                                 Figure 4

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

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

8.  Logical Data Model

   This section identifies 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 Decomposition

8.1.1.  Groups

   The AMA supports four basic groups of information: Data, Actions,
   Literals, and Operators:

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

   Actions Actions are invoked on Agents and Managers to change behavior
           in response to some external event (such as local state
           changes or time).  Actions 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.  Levels

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

           The Atomic level contains items computed or defined
           externally to the AMA and, thus, cannot be changed or
           otherwise decomposed by Actors within the AMA.  These items
           are described in the context of an ADM and implemented in the
           context of firmware or software running on an Agent.  The

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           identification of Atomic items MUST be globally unique and
           should be managed by a registration authority.

           The Computed level contains items whose definition/value are
           specified/computed within the scope of an Actor in the AMA.
           Items at the computed level may be formally specified in an
           ADM (and therefore have definitions that are not subject to
           change) or may be defined dynamically on Agents by Managers
           and therefore have definitions that are subject to change in
           accordance with configuration services.  In either case the
           definition of a Computed level item may reference other
           Computed level items and other Atomic level items if such
           inclusion does not result in a circular reference.  When
           defined in the context of an ADM, a Computed level item MUST
           be globally unique and should be managed by a registration

           The Collection level contains items representing groups of
           other items, including other Collection level items.  When a
           Collection level item definition references another
           Collection level item, circular references MUST be prevented.
           When defined in the context of an ADM, a Collection level
           item MUST be globally unique and should be managed by a
           registration authority.

8.2.  Data Model

   Each component of the AMA data model can be identified as a
   combination of group and level, as illustrated in Table 2.  In this
   table, group/level combinations that are unsupported are listed as N/
   A.  In this context, N/A indicates that the AMA does not require
   support for groups of data at a particular level for compliance.

   |            |         Data         |  Action | Literals | Operator |
   |   Atomic   |  Externally Defined  | Control | Literal  | Operator |
   |            |         Data         |         |          |          |
   |            |                      |         |          |          |
   |  Computed  |       Variable       |   Rule  |   N/A    |   N/A    |
   |            |                      |         |          |          |
   | Collection |     Report Entry     |  Macro  |   N/A    |   N/A    |

                                  Table 2

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

8.2.1.  EDDs, VARs, and Reporting

   Fundamental to any performance reporting function is the ability to
   measure the state of 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.

   EDDs 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 (Variable)
   values in the system.

   AMPs MAY consider the concept of the confidence of the EDD 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.

   While EDDs 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 Entry which
   populates either a pre-defined or ad-hoc Report Template.  In support
   of hierarchical definitions, Report Entries may, themselves, contain
   other Report Entries.  It would be incumbent on an AMP implementation
   to guard against circular reference in Report Template 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 provides well-known identifiers for
   Actions.  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

   Computing values or evaluating expressions requires applying
   mathematical operations to data known to the management system.

   Operators in the AMA represent enumerated mathematical operations
   applied to primitive and computed values 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

   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 Variable, B would be either a Variable or EDD, +
   would be an Operator, and 10 would be a Literal.

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 published interface for the management of an application or
   protocol independent of the nuances of its software implementation.
   In this respect, the ADM is conceptually similar to the Managed

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   Information Base (MIB) used by SNMP, but contains additional
   information relating to command opcodes and more expressive syntax
   for automated behavior.

   An ADM MUST define all well-known items necessary to manage the
   specific application or protocol.  This includes the definitions of
   EDDs, Variables, Report Templates, 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.

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

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   [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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