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Guidelines for Autonomic Service Agents

The information below is for an old version of the document.
Document Type
This is an older version of an Internet-Draft that was ultimately published as RFC 9222.
Authors Brian E. Carpenter , Laurent Ciavaglia , Sheng Jiang , Peloso Pierre
Last updated 2022-01-20 (Latest revision 2021-12-19)
Replaces draft-carpenter-anima-asa-guidelines
RFC stream Internet Engineering Task Force (IETF)
Additional resources Mailing list discussion
Stream WG state Submitted to IESG for Publication
Document shepherd Toerless Eckert
Shepherd write-up Show Last changed 2021-11-18
IESG IESG state Became RFC 9222 (Informational)
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Responsible AD Robert Wilton
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Network Working Group                                    B. E. Carpenter
Internet-Draft                                         Univ. of Auckland
Intended status: Informational                              L. Ciavaglia
Expires: 22 June 2022                                     Rakuten Mobile
                                                                S. Jiang
                                            Huawei Technologies Co., Ltd
                                                               P. Peloso
                                                        19 December 2021

                Guidelines for Autonomic Service Agents


   This document proposes guidelines for the design of Autonomic Service
   Agents for autonomic networks.  Autonomic Service Agents, together
   with the Autonomic Network Infrastructure, the Autonomic Control
   Plane and the Generic Autonomic Signaling Protocol constitute base
   elements of a so-called autonomic networking ecosystem.

Discussion Venue

   This note is to be removed before publishing as an RFC.

   Discussion of this document takes place on the ANIMA mailing list
   (, which is archived at

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

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

   This Internet-Draft will expire on 22 June 2022.

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Copyright Notice

   Copyright (c) 2021 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Logical Structure of an Autonomic Service Agent . . . . . . .   5
   3.  Interaction with the Autonomic Networking Infrastructure  . .   6
     3.1.  Interaction with the security mechanisms  . . . . . . . .   6
     3.2.  Interaction with the Autonomic Control Plane  . . . . . .   6
     3.3.  Interaction with GRASP and its API  . . . . . . . . . . .   7
     3.4.  Interaction with policy mechanisms  . . . . . . . . . . .   8
   4.  Interaction with Non-Autonomic Components . . . . . . . . . .   8
   5.  Design of GRASP Objectives  . . . . . . . . . . . . . . . . .   9
   6.  Life Cycle  . . . . . . . . . . . . . . . . . . . . . . . . .  10
     6.1.  Installation phase  . . . . . . . . . . . . . . . . . . .  11
       6.1.1.  Installation phase inputs and outputs . . . . . . . .  12
     6.2.  Instantiation phase . . . . . . . . . . . . . . . . . . .  12
       6.2.1.  Operator's goal . . . . . . . . . . . . . . . . . . .  13
       6.2.2.  Instantiation phase inputs and outputs  . . . . . . .  13
       6.2.3.  Instantiation phase requirements  . . . . . . . . . .  14
     6.3.  Operation phase . . . . . . . . . . . . . . . . . . . . .  15
   7.  Coordination and Data Models  . . . . . . . . . . . . . . . .  15
     7.1.  Coordination between Autonomic Functions  . . . . . . . .  15
     7.2.  Coordination with Traditional Management Functions  . . .  16
     7.3.  Data Models . . . . . . . . . . . . . . . . . . . . . . .  16
   8.  Robustness  . . . . . . . . . . . . . . . . . . . . . . . . .  16
   9.  Security Considerations . . . . . . . . . . . . . . . . . . .  18
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  19
   11. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  19
   12. References  . . . . . . . . . . . . . . . . . . . . . . . . .  19
     12.1.  Normative References . . . . . . . . . . . . . . . . . .  19
     12.2.  Informative References . . . . . . . . . . . . . . . . .  20
   Appendix A.  Change log . . . . . . . . . . . . . . . . . . . . .  22
   Appendix B.  Terminology  . . . . . . . . . . . . . . . . . . . .  24
   Appendix C.  Example Logic Flows  . . . . . . . . . . . . . . . .  25
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  29

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1.  Introduction

   This document proposes guidelines for the design of Autonomic Service
   Agents (ASAs) in the context of an Autonomic Network (AN) based on
   the Autonomic Network Infrastructure (ANI) outlined in the ANIMA
   reference model [RFC8993].  This infrastructure makes use of the
   Autonomic Control Plane (ACP) [RFC8994] and the Generic Autonomic
   Signaling Protocol (GRASP) [RFC8990].  A general introduction to this
   environment may be found at [IPJ], which also includes explanatory
   diagrams, and a summary of terminology is in Appendix B.

   This document is a contribution to the description of an autonomic
   networking ecosystem, recognizing that a deployable autonomic network
   needs more than just ACP and GRASP implementations.  Such an
   autonomic network must achieve management tasks that a Network
   Operations Center (NOC) cannot readily achieve manually, such as
   continuous resource optimization or automated fault detection and
   repair.  These tasks, and other management automation goals, are
   described at length in [RFC7575].  The net result should be
   significant improvement of operational metrics.  To achieve this, the
   autonomic networking ecosystem must include at least a library of
   ASAs and corresponding GRASP technical objective definitions.  A
   GRASP objective [RFC8990] is a data structure whose main contents are
   a name and a value.  The value consists of a single configurable
   parameter or a set of parameters of some kind.

   There must also be tools to deploy and oversee ASAs, and integration
   with existing operational mechanisms [RFC8368].  However, this
   document focuses on the design of ASAs, with some reference to
   implementation and operational aspects.

   There is a considerable literature about autonomic agents with a
   variety of proposals about how they should be characterized.  Some
   examples are [DeMola06], [Huebscher08], [Movahedi12] and [GANA13].
   However, for the present document, the basic definitions and goals
   for autonomic networking given in [RFC7575] apply.  According to RFC
   7575, an Autonomic Service Agent is "An agent implemented on an
   autonomic node that implements an autonomic function, either in part
   (in the case of a distributed function) or whole."

   ASAs must be distinguished from other forms of software component.
   They are components of network or service management; they do not in
   themselves provide services to end users.  They do however provide
   management services to network operators and administrators.  For
   example, the services envisaged for network function virtualisation
   [RFC8568] or for service function chaining [RFC7665] might be managed
   by an ASA rather than by traditional configuration tools.

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   Another example is that an existing script running within a router to
   locally monitor or configure functions or services could be upgraded
   to an ASA that could communicate with peer scripts on neighboring or
   remote routers.  A high-level API will allow such upgraded scripts to
   take full advantage of the secure ACP and the discovery, negotiation
   and synchronization features of GRASP.  Familiar tasks such as
   configuring an Interior Gateway Protocol (IGP) on neighboring routers
   or even exchanging IGP security keys could be performed securely in
   this way.  This document mainly addresses issues affecting quite
   complex ASAs, but the most useful ones may in fact be rather simple
   developments from existing scripts.

   The reference model [RFC8993] for autonomic networks explains further
   the functionality of ASAs by adding "[An ASA is] a process that makes
   use of the features provided by the ANI to achieve its own goals,
   usually including interaction with other ASAs via the GRASP protocol
   [RFC8990] or otherwise.  Of course, it also interacts with the
   specific targets of its function, using any suitable mechanism.
   Unless its function is very simple, the ASA will need to handle
   overlapping asynchronous operations.  It may therefore be a quite
   complex piece of software in its own right, forming part of the
   application layer above the ANI."

   As mentioned, there will certainly be simple ASAs that manage a
   single objective in a straightforward way and do not need
   asynchronous operations.  In nodes where computing power and memory
   space are limited, ASAs should run at a much lower frequency than the
   primary workload, so CPU load should not be a big issue, but memory
   footprint in a constrained node is certainly a concern.  ASAs
   installed in constrained devices will have limited functionality.  In
   such cases, many aspects of the current document do not apply.
   However, in the general case, an ASA may be a relatively complex
   software component that will in many cases control and monitor
   simpler entities in the same or remote host(s).  For example, a
   device controller that manages tens or hundreds of simple devices
   might contain a single ASA.

   The remainder of this document offers guidance on the design of
   complex ASAs.  Some of the material may be familiar to those
   experienced in distributed fault-tolerant and real-time control

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2.  Logical Structure of an Autonomic Service Agent

   As mentioned above, all but the simplest ASAs will need to support
   asynchronous operations.  Different programming environments support
   asynchronicity in different ways.  In this document, we use an
   explicit multi-threading model to describe operations.  Alternatives
   are discussed in connection with the GRASP API in Section 3.3.

   A typical ASA will have a main thread that performs various initial
   housekeeping actions such as:

   *  Obtain authorization credentials, if needed.

   *  Register the ASA with GRASP.

   *  Acquire relevant policy parameters.

   *  Define data structures for relevant GRASP objectives.

   *  Register with GRASP those objectives that it will actively manage.

   *  Launch a self-monitoring thread.

   *  Enter its main loop.

   The logic of the main loop will depend on the details of the
   autonomic function concerned.  Whenever asynchronous operations are
   required, extra threads may be launched.  Examples of such threads

   *  Repeatedly flood an objective to the AN, so that any ASA can
      receive the objective's latest value.

   *  Accept incoming synchronization requests for an objective managed
      by this ASA.

   *  Accept incoming negotiation requests for an objective managed by
      this ASA, and then conduct the resulting negotiation with the
      counterpart ASA.

   *  Manage subsidiary non-autonomic devices directly.

   These threads should all either exit after their job is done, or
   enter a wait state for new work, to avoid wasting system resources.

   According to the degree of parallelism needed by the application,
   some of these threads might be launched in multiple instances.  In
   particular, if negotiation sessions with other ASAs are expected to

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   be long or to involve wait states, the ASA designer might allow for
   multiple simultaneous negotiating threads, with appropriate use of
   queues and locks to maintain consistency.

   The main loop itself could act as the initiator of synchronization
   requests or negotiation requests, when the ASA needs data or
   resources from other ASAs.  In particular, the main loop should watch
   for changes in policy parameters that affect its operation.  It
   should also do whatever is required to avoid unnecessary resource
   consumption, for example by limiting its frequency of execution.

   The self-monitoring thread is of considerable importance.  Autonomic
   service agents must never fail.  To a large extent this depends on
   careful coding and testing, with no unhandled error returns or
   exceptions, but if there is nevertheless some sort of failure, the
   self-monitoring thread should detect it, fix it if possible, and in
   the worst case restart the entire ASA.

   Appendix C presents some example logic flows in informal pseudocode.

3.  Interaction with the Autonomic Networking Infrastructure

3.1.  Interaction with the security mechanisms

   An ASA by definition runs in an autonomic node.  Before any normal
   ASAs are started, such nodes must be bootstrapped into the autonomic
   network's secure key infrastructure, typically in accordance with
   [RFC8995].  This key infrastructure will be used to secure the ACP
   (next section) and may be used by ASAs to set up additional secure
   interactions with their peers, if needed.

   Note that the secure bootstrap process itself may include special-
   purpose ASAs that run in a constrained insecure mode.

3.2.  Interaction with the Autonomic Control Plane

   In a normal autonomic network, ASAs will run as clients of the ACP,
   which will provide a fully secured network environment for all
   communication with other ASAs, in most cases mediated by GRASP (next

   Note that the ACP formation process itself may include special-
   purpose ASAs that run in a constrained insecure mode.

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3.3.  Interaction with GRASP and its API

   GRASP [RFC8990] is likely to run as a separate process with its API
   [RFC8991] available in user space.  Thus, ASAs may operate without
   special privilege, unless they need it for other reasons.  The ASA's
   view of GRASP is built around GRASP objectives (Section 5), defined
   as data structures containing administrative information such as the
   objective's unique name, and its current value.  The format and size
   of the value is not restricted by the protocol, except that it must
   be possible to serialise it for transmission in Concise Binary Object
   Representation (CBOR) [RFC8949], subject only to GRASP's maximum
   message size as discussed in Section 5.

   As discussed in Section 2, GRASP is an asynchronous protocol, and
   this document uses a multi-threading model to describe operations.
   In many programming environments, an 'event loop' model is used
   instead, in which case each thread would be implemented as an event
   handler called in turn by the main loop.  For this case, the GRASP
   API must provide non-blocking calls and possibly support callbacks.
   This topic is discussed in more detail in [RFC8991], and other
   asynchronicity models are also possible.  Whenever necessary, the
   GRASP session identifier will be used to distinguish simultaneous

   The GRASP API should offer the following features:

   *  Registration functions, so that an ASA can register itself and the
      objectives that it manages.

   *  A discovery function, by which an ASA can discover other ASAs
      supporting a given objective.

   *  A negotiation request function, by which an ASA can start
      negotiation of an objective with a counterpart ASA.  With this,
      there is a corresponding listening function for an ASA that wishes
      to respond to negotiation requests, and a set of functions to
      support negotiating steps.  Once a negotiation starts, it is a
      symmetric process with both sides sending successive objective
      values to each other until agreement is reached (or the
      negotiation fails).

   *  A synchronization function, by which an ASA can request the
      current value of an objective from a counterpart ASA.  With this,
      there is a corresponding listening function for an ASA that wishes
      to respond to synchronization requests.  Unlike negotiation,
      synchronization is an asymmetric process in which the listener
      sends a single objective value to the requester.

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   *  A flood function, by which an ASA can cause the current value of
      an objective to be flooded throughout the AN so that any ASA can
      receive it.

   For further details and some additional housekeeping functions, see

   The GRASP API is intended to support the various interactions
   expected between most ASAs, such as the interactions outlined in
   Section 2.  However, if ASAs require additional communication between
   themselves, they can do so using any desired protocol, such as a TLS
   session over the ACP if that meets their needs.  One option is to use
   GRASP discovery and synchronization as a rendez-vous mechanism
   between two ASAs, passing communication parameters such as a TCP port
   number via GRASP.  As noted above, the ACP should be used to secure
   such communications.

3.4.  Interaction with policy mechanisms

   At the time of writing, the policy mechanisms for the ANI are
   undefined.  In particular, the use of declarative policies (aka
   Intents) for the definition and management of ASA's behaviors remains
   a research topic [I-D.irtf-nmrg-ibn-concepts-definitions].

   In the cases where ASAs are defined as closed control loops, the
   specifications defined in [ZSM009-1] regarding imperative and
   declarative goal statements may be applicable.

   In the ANI, policy dissemination is expected to operate by an
   information distribution mechanism (e.g. via GRASP [RFC8990]) that
   can reach all autonomic nodes, and therefore every ASA.  However,
   each ASA must be capable of operating "out of the box" in the absence
   of locally defined policy, so every ASA implementation must include
   carefully chosen default values and settings for all policy

4.  Interaction with Non-Autonomic Components

   An ASA, to have any external effects, must also interact with non-
   autonomic components of the node where it is installed.  For example,
   an ASA whose purpose is to manage a resource must interact with that
   resource.  An ASA whose purpose is to manage an entity that is
   already managed by local software must interact with that software.
   For example, if such management is performed by NETCONF [RFC6241],
   the ASA must interact with the NETCONF server as an independent
   NETCONF client in the same node to avoid any inconsistency between
   configuration changes delivered via NETCONF and configuration changes
   made by the ASA.

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   In an environment where systems are virtualized and specialized using
   techniques such as network function virtualization or network
   slicing, there will be a design choice whether ASAs are deployed once
   per physical node or once per virtual context.  A related issue is
   whether the ANI as a whole is deployed once on a physical network, or
   whether several virtual ANIs are deployed.  This aspect needs to be
   considered by the ASA designer.

5.  Design of GRASP Objectives

   The general rules for the format of GRASP objectives, their names,
   and IANA registration are given in [RFC8990].  Additionally, that
   document discusses various general considerations for the design of
   objectives, which are not repeated here.  However, note that the
   GRASP protocol, like HTTP, does not provide transactional integrity.
   In particular, steps in a GRASP negotiation are not idempotent.  The
   design of a GRASP objective and the logic flow of the ASA should take
   this into account.  One approach, which should be used when possible,
   is to design objectives with idempotent semantics.  If this is not
   possible, typically if an ASA is allocating part of a shared resource
   to other ASAs, it needs to ensure that the same part of the resource
   is not allocated twice.  The easiest way is to run only one
   negotiation at a time.  If an ASA is capable of overlapping several
   negotiations, it must avoid interference between these negotiations.

   Negotiations will always end, normally because one end or the other
   declares success or failure.  If this does not happen, either a
   timeout or exhaustion of the loop count will occur.  The definition
   of a GRASP objective should describe a specific negotiation policy if
   it is not self-evident.

   GRASP allows a 'dry run' mode of negotiation, where a negotiation
   session follows its normal course but is not committed at either end
   until a subsequent live negotiation session.  If 'dry run' mode is
   defined for the objective, its specification, and every
   implementation, must consider what state needs to be saved following
   a dry run negotiation, such that a subsequent live negotiation can be
   expected to succeed.  It must be clear how long this state is kept,
   and what happens if the live negotiation occurs after this state is
   deleted.  An ASA that requests a dry run negotiation must take
   account of the possibility that a successful dry run is followed by a
   failed live negotiation.  Because of these complexities, the dry run
   mechanism should only be supported by objectives and ASAs where there
   is a significant benefit from it.

   The actual value field of an objective is limited by the GRASP
   protocol definition to any data structure that can be expressed in
   Concise Binary Object Representation (CBOR) [RFC8949].  For some

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   objectives, a single data item will suffice; for example an integer,
   a floating point number or a UTF-8 string.  For more complex cases, a
   simple tuple structure such as [item1, item2, item3] could be used.
   Since CBOR is closely linked to JSON, it is also rather easy to
   define an objective whose value is a JSON structure.  The formats
   acceptable by the GRASP API will limit the options in practice.  A
   generic solution is for the API to accept and deliver the value field
   in raw CBOR, with the ASA itself encoding and decoding it via a CBOR

   The maximum size of the value field of an objective is limited by the
   GRASP maximum message size.  If the default maximum size specified by
   [RFC8990] is not enough, the specification of the objective must
   indicate the required maximum message size, both for unicast and
   multicast messages.

   A mapping from YANG to CBOR is defined by [I-D.ietf-core-yang-cbor].
   Subject to the size limit defined for GRASP messages, nothing
   prevents objectives using YANG in this way.

   It is expected that the value field of many objectives will be
   extended in service, to add additional information.  This has
   consequences for the robustness of ASAs, as discussed in Section 8.

6.  Life Cycle

   The ASA life cycle was discussed in
   [I-D.peloso-anima-autonomic-function], from which the following text
   was derived.

   In simple cases, Autonomic functions could be permanent, in the sense
   that ASAs are shipped as part of a product and persist throughout the
   product's life.  However, in complex cases, a more likely situation
   is that ASAs need to be installed or updated dynamically, because of
   new requirements or bugs.  This section describes one approach to the
   resulting life cycle.

   Because continuity of service is fundamental to autonomic networking,
   the process of seamlessly replacing a running instance of an ASA with
   a new version needs to be part of the ASA's design.  The implication
   of service continuity on the design of ASAs can be illustrated along
   the three main phases of the ASA life cycle, namely Installation,
   Instantiation and Operation.

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   Undeployed ------>|              |------> Undeployed
                     |  Installed   |
                 +-->|              |---+
        Mandate  |   +--------------+   | Receives a
      is revoked |   +--------------+   |  Mandate
                 +---|              |<--+
                     | Instantiated |
                 +-->|              |---+
             set |   +--------------+   | set
            down |   +--------------+   | up
                 +---|              |<--+
                     |  Operational |
                     |              |

             Figure 1: Life Cycle of an Autonomic Service Agent

6.1.  Installation phase

   We define "installation" to mean that a piece of software is loaded
   into a device, along with any necessary libraries, but is not yet

   Before being able to instantiate and run ASAs, the operator will
   first provision the infrastructure with the sets of ASA software
   corresponding to its needs and objectives.  The provisioning of the
   infrastructure is realized in the installation phase and consists in
   installing (or checking the availability of) the pieces of software
   of the different ASAs in a set of Installation Hosts.  Installation
   Hosts may be nodes of an autonomic network, or servers dedicated to
   storing the software images of the different ASAs.

   There are 3 properties applicable to the installation of ASAs:

   *  The dynamic installation property allows installing an ASA on
      demand, on any hosts compatible with the ASA.

   *  The decoupling property allows controlling resources of an
      autonomic node from a remote ASA, i.e. an ASA installed on a host
      machine different from the autonomic node resources.

   *  The multiplicity property allows controlling multiple sets of
      resources from a single ASA.

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   These three properties are very important in the context of the
   installation phase as their variations condition how the ASA could be
   installed on the infrastructure.

6.1.1.  Installation phase inputs and outputs

   Inputs are:

   *  [ASA of a given type] specifies which ASAs to install.

   *  [Installation_target_Infrastructure] specifies the candidate
      Installation Hosts.

   *  [ASA placement function] specifies how the installation phase will
      meet the operator's needs and objectives for the provision of the
      infrastructure.  This function is only required in the decoupled
      mode.  It can be as simple as an explicit list of Installation
      Hosts, or it could consist of operator-defined criteria and

   The main output of the installation phase is a [list of ASAs]
   installed on [list of Installation Hosts].  This output is also
   useful for the coordination function where it acts as a static
   interaction map (see Section 7.1).

   The condition to validate in order to pass to next phase is to ensure
   that [list of ASAs] are well installed on [list of Installation
   Hosts].  The state of the ASAs at the end of the installation phase
   is installed (but not instantiated).  A minimum set of primitives to
   support the installation of ASAs could be: install(list of ASAs,
   Installation_target_Infrastructure, ASA placement function), and
   uninstall (list of ASAs).

6.2.  Instantiation phase

   We define "instantiation" as the operation of creating a single ASA
   instance from the corresponding piece of installed software.

   Once the ASAs are installed on the appropriate hosts in the network,
   these ASAs may start to operate.  From the operator viewpoint, an
   operating ASA means the ASA manages the network resources as per the
   objectives given.  At the ASA local level, operating means executing
   their control loop algorithm.

   But right before that, there are two things to take into
   consideration.  First, there is a difference between (1) having a
   piece of code available to run on a host and (2) having an agent
   based on this piece of code running inside the host.  Second, in a

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   coupled case, determining which resources are controlled by an ASA is
   straightforward (the ASA runs on the same autonomic node as the
   resources it is controlling); in a decoupled mode determining this is
   a bit more complex: a starting agent will have to either discover the
   set of resources it ought to control, or such information has to be
   communicated to the ASA.

   The instantiation phase of an ASA covers both these aspects: starting
   the agent code (when this does not start automatically) and
   determining which resources have to be controlled (when this is not

6.2.1.  Operator's goal

   Through this phase, the operator wants to control its autonomic
   network regarding at least two aspects:

   1  determine the scope of autonomic functions by instructing which
      network resources have to be managed by which autonomic function
      (and more precisely by which release of the ASA software code,
      e.g., version number or provider),

   2  determine how the autonomic functions are organized by
      instantiating a set of ASAs across one or more autonomic nodes and
      instructing them accordingly about the other ASAs in the set as

   In this phase, the operator may also want to set goals for autonomic
   functions, e.g., by configuring GRASP objectives.

   The operator's goal can be summarized in an instruction to the ANIMA
   ecosystem matching the following format, explained in detail in the
   next sub-section:

      [instances of ASAs of a given type] ready to control
      [Instantiation_target_Infrastructure] with

6.2.2.  Instantiation phase inputs and outputs

   Inputs are:

   *  [instances of ASAs of a given type] that specifies which ASAs to

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   *  [Instantiation_target_Infrastructure] that specifies which are the
      resources to be managed by the autonomic function; this can be the
      whole network or a subset of it like a domain, a physical segment
      or even a specific list of resources,

   *  [Instantiation_target_parameters] that specifies which are the
      GRASP objectives to be sent to ASAs (e.g., an optimization target)

   Outputs are:

   *  [Set of ASAs - Resources relations] describing which resources are
      managed by which ASA instances, this is not a formal message, but
      a resulting configuration of a set of ASAs.

6.2.3.  Instantiation phase requirements

   The instructions described in Section 6.2 could be either:

   *  Sent to a targeted ASA.  In the case, the receiving Agent will
      have to manage the specified list of
      [Instantiation_target_Infrastructure], with the

   *  Broadcast to all ASAs.  In this case, the ASAs would collectively
      determine from the list which Agent(s) would handle which
      [Instantiation_target_Infrastructure], with the

   These instructions may be grouped as a specific data structure,
   referred to as an ASA Instance Mandate.  The specification of such an
   ASA Instance Mandate is beyond the scope of this document.

   The conclusion of this instantiation phase is a set of ASA instances
   ready to operate.  These ASA instances are characterized by the
   resources they manage, the metrics being monitored and the actions
   that can be executed (like modifying certain parameters values).  The
   description of the ASA instance may be defined in an ASA Instance
   Manifest data structure.  The specification of such an ASA Instance
   Manifest is beyond the scope of this document.

   The ASA Instance Manifest does not only serve informational purposes
   such as acknowledgement of successful instantiation to the operator,
   but is also necessary for further autonomic operations with:

   *  coordinated entities (see Section 7.1)

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   *  collaborative entities with purposes such as to establish
      knowledge exchange (some ASAs may produce knowledge or monitor
      metrics that would be useful for other ASAs)

6.3.  Operation phase

   During the Operation phase, the operator can:

   *  Activate/Deactivate ASAs: enable/disable their autonomic loops.

   *  Modify ASAs targets: set different technical objectives.

   *  Modify ASAs managed resources: update the instance mandate to
      specify a different set of resources to manage (only applicable to
      decoupled ASAs).

   During the Operation phase, running ASAs can interact with other

   *  in order to exchange knowledge (e.g. an ASA providing traffic
      predictions to a load balancing ASA)

   *  in order to collaboratively reach an objective (e.g.  ASAs
      pertaining to the same autonomic function will collaborate, e.g.,
      in the case of a load balancing function, by modifying link
      metrics according to neighboring resource loads)

   During the Operation phase, running ASAs are expected to apply
   coordination schemes as per Section 7.1.

7.  Coordination and Data Models

7.1.  Coordination between Autonomic Functions

   Some autonomic functions will be completely independent of each
   other.  However, others are at risk of interfering with each other -
   for example, two different optimization functions might both attempt
   to modify the same underlying parameter in different ways.  In a
   complete system, a method is needed of identifying ASAs that might
   interfere with each other and coordinating their actions when
   necessary.  This issue is considered in detail in

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7.2.  Coordination with Traditional Management Functions

   Some ASAs will have functions that overlap with existing
   configuration tools and network management mechanisms such as command
   line interfaces, DHCP, DHCPv6, SNMP, NETCONF, and RESTCONF.  This is
   of course an existing problem whenever multiple configuration tools
   are in use by the NOC.  Each ASA designer will need to consider this
   issue and how to avoid clashes and inconsistencies.  Some specific
   considerations for interaction with OAM tools are given in [RFC8368].
   As another example, [RFC8992] describes how autonomic management of
   IPv6 prefixes can interact with prefix delegation via DHCPv6.  The
   description of a GRASP objective and of an ASA using it should
   include a discussion of any such interactions.

7.3.  Data Models

   Management functions often include a shared data model, quite likely
   to be expressed in a formal notation such as YANG.  This aspect
   should not be an afterthought in the design of an ASA.  To the
   contrary, the design of the ASA and of its GRASP objectives should
   match the data model; as noted in Section 5, YANG serialized as CBOR
   may be used directly as the value of a GRASP objective.

8.  Robustness

   It is of great importance that all components of an autonomic system
   are highly robust.  Although ASA designers should aim for their
   component to never fail, it is more important to design the ASA to
   assume that failures will happen and to gracefully recover from those
   failures when they occur.  Hence, this section lists various aspects
   of robustness that ASA designers should consider:

   1.   If despite all precautions, an ASA does encounter a fatal error,
        it should in any case restart automatically and try again.  To
        mitigate a loop in case of persistent failure, a suitable pause
        should be inserted before such a restart.  The length of the
        pause depends on the use case.

   2.   If a newly received or calculated value for a parameter falls
        out of bounds, the corresponding parameter should be either left
        unchanged or restored to a safe value.

   3.   If a GRASP synchronization or negotiation session fails for any
        reason, it may be repeated after a suitable pause.  The length
        of the pause depends on the use case.

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   4.   If a session fails repeatedly, the ASA should consider that its
        peer has failed, and cause GRASP to flush its discovery cache
        and repeat peer discovery.

   5.   In any case, it may be prudent to repeat discovery periodically,
        depending on the use case.

   6.   Any received GRASP message should be checked.  If it is wrongly
        formatted, it should be ignored.  Within a unicast session, an
        Invalid message (M_INVALID) may be sent.  This function may be
        provided by the GRASP implementation itself.

   7.   Any received GRASP objective should be checked.  Basic
        formatting errors like invalid CBOR will likely be detected by
        GRASP itself, but the ASA is responsible for checking the
        precise syntax and semantics of a received objective.  If it is
        wrongly formatted, it should be ignored.  Within a negotiation
        session, a Negotiation End message (M_END) with a Decline option
        (O_DECLINE) should be sent.  An ASA may log such events for
        diagnostic purposes.

   8.   On the other hand, the definitions of GRASP objectives are very
        likely to be extended, using the flexibility of CBOR or JSON.
        Therefore, ASAs should be able to deal gracefully with unknown
        components within the values of objectives.  The specification
        of an objective should describe how unknown components are to be
        handled (ignored, logged and ignored, or rejected as an error).

   9.   If an ASA receives either an Invalid message (M_INVALID) or a
        Negotiation End message (M_END) with a Decline option
        (O_DECLINE), one possible reason is that the peer ASA does not
        support a new feature of either GRASP or of the objective in
        question.  In such a case the ASA may choose to repeat the
        operation concerned without using that new feature.

   10.  All other possible exceptions should be handled in an orderly
        way.  There should be no such thing as an unhandled exception
        (but see point 1 above).

   At a slightly more general level, ASAs are not services in
   themselves, but they automate services.  This has a fundamental
   impact on how to design robust ASAs.  In general, when an ASA
   observes a particular state (1) of operations of the services/
   resources it controls, it typically aims to improve this state to a
   better state, say (2).  Ideally, the ASA is built so that it can
   ensure that any error encountered can still lead to returning to (1)
   instead of a state (3) which is worse than (1).  One example instance
   of this principle is "make-before-break" used in reconfiguration of

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   routing protocols in manual operations.  This principle of operations
   can accordingly be coded into the operation of an ASA.  The GRASP dry
   run option mentioned in Section 5 is another tool helpful for this
   ASA design goal of "test-before-make".

9.  Security Considerations

   ASAs are intended to run in an environment that is protected by the
   Autonomic Control Plane [RFC8994], admission to which depends on an
   initial secure bootstrap process such as BRSKI [RFC8995].  Such an
   ACP can provide keying material for mutual authentication between
   ASAs as well as confidential communication channels for messages
   between ASAs.  In some deployments, a secure partition of the link
   layer might be used instead.  However, this does not relieve ASAs of
   responsibility for security.  When ASAs configure or manage network
   elements outside the ACP, potentially in a different physical node,
   they must interact with other non-autonomic software components to
   perform their management functions.  The details are specific to each
   case, but this has an important security implication.  An ASA might
   act as a loophole by which the managed entity could penetrate the
   security boundary of the ANI.  Thus, ASAs must be designed to avoid
   loopholes such as passing on executable code, and should if possible
   operate in an unprivileged mode.  In particular, they must use secure
   coding practices, e.g., carefully validate all incoming information
   and avoid unnecessary elevation of privilege.  This will apply in
   particular when an ASA interacts with a management component such as
   a NETCONF server.

   A similar situation will arise if an ASA acts as a gateway between
   two separate autonomic networks, i.e. it has access to two separate
   ACPs.  Such an ASA must also be designed to avoid loopholes and to
   validate incoming information from both sides.

   As appropriate to their specific functions, ASAs should take account
   of relevant privacy considerations [RFC6973].

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   The initial version of the autonomic infrastructure assumes that all
   autonomic nodes are trusted by virtue of their admission to the ACP.
   ASAs are therefore trusted to manipulate any GRASP objective, simply
   because they are installed on a node that has successfully joined the
   ACP.  In the general case, a node may have multiple roles and a role
   may use multiple ASAs, each using multiple GRASP objectives.
   Additional mechanisms for the fine-grained authorization of nodes and
   ASAs to manipulate specific GRASP objectives could be designed.
   Independently of this, interfaces between ASAs and the router
   configuration and monitoring services of the node can be subject to
   authentication that provides more fine-grained authorization for
   specific services.  These additional authentication parameters could
   be passed to an ASA during its instantiation phase.

10.  IANA Considerations

   This document makes no request of the IANA.

11.  Acknowledgements

   Valuable comments were received from Michael Behringer, Menachem
   Dodge, Martin Dürst, Toerless Eckert, Thomas Fossati, Alex Galis,
   Bing Liu, Michael Richardson, and Rob Wilton.

12.  References

12.1.  Normative References

   [RFC8949]  Bormann, C. and P. Hoffman, "Concise Binary Object
              Representation (CBOR)", STD 94, RFC 8949,
              DOI 10.17487/RFC8949, December 2020,

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

   [RFC8994]  Eckert, T., Ed., Behringer, M., Ed., and S. Bjarnason, "An
              Autonomic Control Plane (ACP)", RFC 8994,
              DOI 10.17487/RFC8994, May 2021,

   [RFC8995]  Pritikin, M., Richardson, M., Eckert, T., Behringer, M.,
              and K. Watsen, "Bootstrapping Remote Secure Key
              Infrastructure (BRSKI)", RFC 8995, DOI 10.17487/RFC8995,
              May 2021, <>.

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12.2.  Informative References

   [DeMola06] De Mola, F. and R. Quitadamo, "An Agent Model for Future
              Autonomic Communications", Proceedings of the 7th WOA 2006
              Workshop From Objects to Agents 51-59, September 2006.

   [GANA13]   "Autonomic network engineering for the self-managing
              Future Internet (AFI): GANA Architectural Reference Model
              for Autonomic Networking, Cognitive Networking and Self-
              Management.", April 2013,

              Huebscher, M. C. and J. A. McCann, "A survey of autonomic
              computing - degrees, models, and applications", ACM
              Computing Surveys (CSUR) Volume 40 Issue 3 DOI:
              10.1145/1380584.1380585, August 2008.

              Ciavaglia, L. and P. Pierre, "Autonomic Functions
              Coordination", Work in Progress, Internet-Draft, draft-
              ciavaglia-anima-coordination-01, 21 March 2016,

              Veillette, M., Petrov, I., Pelov, A., Bormann, C., and M.
              Richardson, "CBOR Encoding of Data Modeled with YANG",
              Work in Progress, Internet-Draft, draft-ietf-core-yang-
              cbor-17, 25 October 2021,

              Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
              Tantsura, "Intent-Based Networking - Concepts and
              Definitions", Work in Progress, Internet-Draft, draft-
              irtf-nmrg-ibn-concepts-definitions-06, 15 December 2021,

              Pierre, P. and L. Ciavaglia, "A Day in the Life of an
              Autonomic Function", Work in Progress, Internet-Draft,
              draft-peloso-anima-autonomic-function-01, 21 March 2016,

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   [IPJ]      Behringer, M., Bormann, C., Carpenter, B. E., Eckert, T.,
              Campos Nobre, J., Jiang, S., Li, Y., and M. C. Richardson,
              "Autonomic Networking Gets Serious", The Internet Protocol
              Journal Volume: 24 , Issue: 3, ISSN 1944-1134, Page(s): 2
              - 18, October 2021, <

              Movahedi, Z., Ayari, M., Langar, R., and G. Pujolle, "A
              Survey of Autonomic Network Architectures and Evaluation
              Criteria", IEEE Communications Surveys & Tutorials Volume:
              14 , Issue: 2 DOI: 10.1109/SURV.2011.042711.00078,
              Page(s): 464 - 490, 2012.

   [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,

   [RFC6973]  Cooper, A., Tschofenig, H., Aboba, B., Peterson, J.,
              Morris, J., Hansen, M., and R. Smith, "Privacy
              Considerations for Internet Protocols", RFC 6973,
              DOI 10.17487/RFC6973, July 2013,

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

   [RFC7665]  Halpern, J., Ed. and C. Pignataro, Ed., "Service Function
              Chaining (SFC) Architecture", RFC 7665,
              DOI 10.17487/RFC7665, October 2015,

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

   [RFC8568]  Bernardos, CJ., Rahman, A., Zuniga, JC., Contreras, LM.,
              Aranda, P., and P. Lynch, "Network Virtualization Research
              Challenges", RFC 8568, DOI 10.17487/RFC8568, April 2019,

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   [RFC8991]  Carpenter, B., Liu, B., Ed., Wang, W., and X. Gong,
              "GeneRic Autonomic Signaling Protocol Application Program
              Interface (GRASP API)", RFC 8991, DOI 10.17487/RFC8991,
              May 2021, <>.

   [RFC8992]  Jiang, S., Ed., Du, Z., Carpenter, B., and Q. Sun,
              "Autonomic IPv6 Edge Prefix Management in Large-Scale
              Networks", RFC 8992, DOI 10.17487/RFC8992, May 2021,

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

   [ZSM009-1] "Zero-touch network and Service Management (ZSM); Closed-
              Loop Automation; Part 1: Enablers", June 2021,

Appendix A.  Change log

   This section is to be removed before publishing as an RFC.

   draft-ietf-anima-asa-guidelines-05, 2021-12-20:

   *  Clarified NETCONF wording.
   *  Removed <CODE BEGINS> on advice from IETF Trust
   *  Noted resource limits in constrained nodes
   *  Strengthened text on data integrity in resource management example
   *  Strengthen discussion of extensibility of GRASP objectives.
   *  Other editorial improvements from IETF Last Call reviews

   draft-ietf-anima-asa-guidelines-04, 2021-11-20:

   *  Added terminology appendix
   *  Further clarified discussion of asynch operations
   *  Other editorial improvements from AD review

   draft-ietf-anima-asa-guidelines-03, 2021-11-07:

   *  Added security consideration for gateway ASAs
   *  Cite IPJ article

   draft-ietf-anima-asa-guidelines-02, 2021-09-13:

   *  Added note on maximum message size.
   *  Editorial fixes

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   draft-ietf-anima-asa-guidelines-01, 2021-06-27:

   *  Incorporated shepherd's review comments
   *  Editorial fixes

   draft-ietf-anima-asa-guidelines-00, 2020-11-14:

   *  Adopted by WG
   *  Editorial fixes

   draft-carpenter-anima-asa-guidelines-09, 2020-07-25:

   *  Additional text on future authorization.
   *  Editorial fixes

   draft-carpenter-anima-asa-guidelines-08, 2020-01-10:

   *  Introduced notion of autonomic ecosystem.
   *  Minor technical clarifications.
   *  Converted to v3 format.

   draft-carpenter-anima-asa-guidelines-07, 2019-07-17:

   *  Improved explanation of threading vs event-loop
   *  Other editorial improvements.

   draft-carpenter-anima-asa-guidelines-06, 2018-01-07:

   *  Expanded and improved example logic flow.
   *  Editorial corrections.

   draft-carpenter-anima-asa-guidelines-05, 2018-06-30:

   *  Added section on relationshp with non-autonomic components.
   *  Editorial corrections.

   draft-carpenter-anima-asa-guidelines-04, 2018-03-03:

   *  Added note about simple ASAs.
   *  Added note about NFV/SFC services.
   *  Improved text about threading v event loop model
   *  Added section about coordination with traditional tools.
   *  Added appendix with example logic flow.

   draft-carpenter-anima-asa-guidelines-03, 2017-10-25:

   *  Added details on life cycle.
   *  Added details on robustness.

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   *  Added co-authors.

   draft-carpenter-anima-asa-guidelines-02, 2017-07-01:

   *  Expanded description of event-loop case.
   *  Added note about 'dry run' mode.

   draft-carpenter-anima-asa-guidelines-01, 2017-01-06:

   *  More sections filled in.

   draft-carpenter-anima-asa-guidelines-00, 2016-09-30:

   *  Initial version

Appendix B.  Terminology

   This appendix summarises various acronyms and terminology used in the
   document.  Where no other reference is given, please consult
   [RFC8993] or [RFC7575].

   *  Autonomic: Self-managing (self-configuring, self-protecting, self-
      healing, self-optimizing), but allowing high-level guidance by a
      central entity such as a NOC.
   *  Autonomic Function: A function that adapts on its own to a
      changing environment.
   *  Autonomic Node: A node that employs autonomic functions.
   *  Autonomic Domain: A collection of autonomic nodes that
   *  ACP: Autonomic Control Plane [RFC8994].
   *  AN: Autonomic Network, which underlies an autonomic domain.
   *  ANI: Autonomic Network Infrastructure.
   *  ASA: Autonomic Service Agent.  An agent installed on an autonomic
      node that implements an autonomic function, either partially (in
      the case of a distributed function) or completely.
   *  BRSKI: Bootstrapping Remote Secure Key Infrastructure [RFC8995].
   *  CBOR: Concise Binary Object Representation [RFC8949].
   *  GRASP: Generic Autonomic Signaling Protocol [RFC8990].
   *  GRASP API: GRASP Application Programming Interface [RFC8991].
   *  NOC: Network Operations Center [RFC8368].
   *  Objective: A GRASP technical objective is a data structure whose
      main contents are a name and a value.  The value consists of a
      single configurable parameter or a set of parameters of some kind.

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Appendix C.  Example Logic Flows

   This appendix describes generic logic flows that combine to act as an
   Autonomic Service Agent (ASA) for resource management.  Note that
   these are illustrative examples, and in no sense requirements.  As
   long as the rules of GRASP are followed, a real implementation could
   be different.  The reader is assumed to be familiar with GRASP
   [RFC8990] and its conceptual API [RFC8991].

   A complete autonomic function for a distributed resource will consist
   of a number of instances of the ASA placed at relevant points in a
   network.  Specific details will of course depend on the resource
   concerned.  One example is IP address prefix management, as specified
   in [RFC8992].  In this case, an instance of the ASA will exist in
   each delegating router.

   An underlying assumption is that there is an initial source of the
   resource in question, referred to here as an origin ASA.  The other
   ASAs, known as delegators, obtain supplies of the resource from the
   origin, and then delegate quantities of the resource to consumers
   that request it, and recover it when no longer needed.

   Another assumption is there is a set of network wide policy
   parameters, which the origin will provide to the delegators.  These
   parameters will control how the delegators decide how much resource
   to provide to consumers.  Thus, the ASA logic has two operating
   modes: origin and delegator.  When running as an origin, it starts by
   obtaining a quantity of the resource from the NOC, and it acts as a
   source of policy parameters, via both GRASP flooding and GRASP
   synchronization.  (In some scenarios, flooding or synchronization
   alone might be sufficient, but this example includes both.)

   When running as a delegator, it starts with an empty resource pool,
   it acquires the policy parameters by GRASP synchronization, and it
   delegates quantities of the resource to consumers that request it.
   Both as an origin and as a delegator, when its pool is low it seeks
   quantities of the resource by requesting GRASP negotiation with peer
   ASAs.  When its pool is sufficient, it hands out resource to peer
   ASAs in response to negotiation requests.  Thus, over time, the
   initial resource pool held by the origin will be shared among all the
   delegators according to demand.

   In theory a network could include any number of origins and any
   number of delegators, with the only condition being that each
   origin's initial resource pool is unique.  A realistic scenario is to
   have exactly one origin and as many delegators as you like.  A
   scenario with no origin is useless.

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   An implementation requirement is that resource pools are kept in
   stable storage.  Otherwise, if a delegator exits for any reason, all
   the resources it has obtained or delegated are lost.  If an origin
   exits, its entire spare pool is lost.  The logic for using stable
   storage and for crash recovery is not included in the pseudocode
   below, which focuses on communication between ASAs.  Since GRASP
   operations are not intrinsically idempotent, data integrity during
   failure scenarios is the responsibility of the ASA designer.  This is
   a complex topic in its own right that is not discussed in the present

   The description below does not implement GRASP's 'dry run' function.
   That would require temporarily marking any resource handed out in a
   dry run negotiation as reserved, until either the peer obtains it in
   a live run, or a suitable timeout occurs.

   The main data structures used in each instance of the ASA are:

   *  The resource_pool, for example an ordered list of available
      resources.  Depending on the nature of the resource, units of
      resource are split when appropriate, and a background garbage
      collector recombines split resources if they are returned to the

   *  The delegated_list, where a delegator stores the resources it has
      given to subsidiary devices.

   Possible main logic flows are below, using a threaded implementation
   model.  The transformation to an event loop model should be apparent
   - each thread would correspond to one event in the event loop.

   The GRASP objectives are as follows:

   *  ["EX1.Resource", flags, loop_count, value] where the value depends
      on the resource concerned, but will typically include its size and

   *  ["EX1.Params", flags, loop_count, value] where the value will be,
      for example, a JSON object defining the applicable parameters.

   In the outline logic flows below, these objectives are represented
   simply by their names.

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   Create empty resource_pool (and an associated lock)
   Create empty delegated_list
   Determine whether to act as origin
   if origin:
       Obtain initial resource_pool contents from NOC
       Obtain value of EX1.Params from NOC
   Register ASA with GRASP
   Register GRASP objectives EX1.Resource and EX1.Params
   if origin:
       Start FLOODER thread to flood EX1.Params
       Start SYNCHRONIZER listener for EX1.Params
   Start MAIN_NEGOTIATOR thread for EX1.Resource
   if not origin:
       Obtain value of EX1.Params from GRASP flood or synchronization
       Start DELEGATOR thread
   good_peer = none
   do forever:
       if resource_pool is low:
           Calculate amount A of resource needed
           Discover peers using GRASP M_DISCOVER / M_RESPONSE
           if good_peer in peers:
               peer = good_peer
               peer =  #any choice among peers
               grasp.request_negotiate("EX1.Resource", peer)
               #i.e., send negotiation request
               Wait for response (M_NEGOTIATE, M_END or M_WAIT)
               if OK:
                   if offered amount of resource sufficient:
                       Send M_END + O_ACCEPT #negotiation succeeded
                       Add resource to pool
                       good_peer = peer      #remember this choice
                       Send M_END + O_DECLINE #negotiation failed
       sleep() #periodic timer suitable for application scenario


   do forever:
       #i.e., wait for negotiation request
       Start a separate new NEGOTIATOR thread for requested amount A

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   NEGOTIATOR thread:

   Request resource amount A from resource_pool
   if not OK:
       while not OK and A > Amin:
           A = A-1
           Request resource amount A from resource_pool
   if OK:
       Offer resource amount A to peer by GRASP M_NEGOTIATE
       if received M_END + O_ACCEPT:
           #negotiation succeeded
       elif received M_END + O_DECLINE or other error:
           #negotiation failed
       Send M_END + O_DECLINE #negotiation failed
   #thread exits

   DELEGATOR thread:

   do forever:
       Wait for request or release for resource amount A
       if request:
           Get resource amount A from resource_pool
           if OK:
               Delegate resource to consumer #atomic
               Record in delegated_list      #operation
               Signal failure to consumer
               Signal main thread that resource_pool is low
           Delete resource from delegated_list
           Return resource amount A to resource_pool


   do forever:
       Wait for  M_REQ_SYN message for EX1.Params
       Reply with M_SYNCH message for EX1.Params

   FLOODER thread:

   do forever:
       Send M_FLOOD message for EX1.Params
       sleep() #periodic timer suitable for application scenario

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   do forever:
       Search resource_pool for adjacent resources
       Merge adjacent resources
       sleep() #periodic timer suitable for application scenario

Authors' Addresses

   Brian Carpenter
   School of Computer Science
   University of Auckland
   PB 92019
   Auckland 1142
   New Zealand


   Laurent Ciavaglia
   Rakuten Mobile


   Sheng Jiang
   Huawei Technologies Co., Ltd
   Q14 Huawei Campus
   156 Beiqing Road
   Hai-Dian District


   Pierre Peloso
   91460 Nozay


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