draft-ietf-anima-reference-model-07.txt

ANIMA                                                  M. Behringer, Ed.
Internet-Draft
Intended status: Informational                              B. Carpenter
Expires: February 25, 2019                             Univ. of Auckland
                                                               T. Eckert
                                             Futurewei Technologies Inc.
                                                            L. Ciavaglia
                                                                   Nokia
                                                                J. Nobre
                                     University of Vale do Rio dos Sinos
                                                         August 24, 2018


               A Reference Model for Autonomic Networking
                  draft-ietf-anima-reference-model-07

Abstract

   This document describes a reference model for Autonomic Networking
   for managed networks.  It defines the behaviour of an autonomic node,
   how the various elements in an autonomic context work together, and
   how autonomic services can use the infrastructure.

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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   Internet-Drafts are draft documents valid for a maximum of six months
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   This Internet-Draft will expire on February 25, 2019.

Copyright Notice

   Copyright (c) 2018 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
   (https://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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   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  The Network View  . . . . . . . . . . . . . . . . . . . . . .   4
   3.  The Autonomic Network Element . . . . . . . . . . . . . . . .   5
     3.1.  Architecture  . . . . . . . . . . . . . . . . . . . . . .   5
     3.2.  The Adjacency Table . . . . . . . . . . . . . . . . . . .   6
     3.3.  State Machine . . . . . . . . . . . . . . . . . . . . . .   8
       3.3.1.  State 1: Factory Default  . . . . . . . . . . . . . .   8
       3.3.2.  State 2: Enrolled . . . . . . . . . . . . . . . . . .   9
       3.3.3.  State 3: In ACP . . . . . . . . . . . . . . . . . . .   9
   4.  The Autonomic Networking Infrastructure . . . . . . . . . . .  10
     4.1.  Naming  . . . . . . . . . . . . . . . . . . . . . . . . .  10
     4.2.  Addressing  . . . . . . . . . . . . . . . . . . . . . . .  10
     4.3.  Discovery . . . . . . . . . . . . . . . . . . . . . . . .  11
     4.4.  Signaling Between Autonomic Nodes . . . . . . . . . . . .  12
     4.5.  Routing . . . . . . . . . . . . . . . . . . . . . . . . .  13
     4.6.  The Autonomic Control Plane . . . . . . . . . . . . . . .  13
     4.7.  Information Distribution (*)  . . . . . . . . . . . . . .  13
   5.  Security and Trust Infrastructure . . . . . . . . . . . . . .  14
     5.1.  Public Key Infrastructure . . . . . . . . . . . . . . . .  14
     5.2.  Domain Certificate  . . . . . . . . . . . . . . . . . . .  14
     5.3.  The MASA  . . . . . . . . . . . . . . . . . . . . . . . .  14
     5.4.  Sub-Domains (*) . . . . . . . . . . . . . . . . . . . . .  15
     5.5.  Cross-Domain Functionality (*)  . . . . . . . . . . . . .  15
   6.  Autonomic Service Agents (ASA)  . . . . . . . . . . . . . . .  15
     6.1.  General Description of an ASA . . . . . . . . . . . . . .  15
     6.2.  ASA Life-Cycle Management . . . . . . . . . . . . . . . .  17
     6.3.  Specific ASAs for the Autonomic Network Infrastructure  .  18
       6.3.1.  The enrollment ASAs . . . . . . . . . . . . . . . . .  18
       6.3.2.  The ACP ASA . . . . . . . . . . . . . . . . . . . . .  18
       6.3.3.  The Information Distribution ASA (*)  . . . . . . . .  19
   7.  Management and Programmability  . . . . . . . . . . . . . . .  19
     7.1.  Managing a (Partially) Autonomic Network  . . . . . . . .  19
     7.2.  Intent (*)  . . . . . . . . . . . . . . . . . . . . . . .  20
     7.3.  Aggregated Reporting (*)  . . . . . . . . . . . . . . . .  20
     7.4.  Feedback Loops to NOC (*) . . . . . . . . . . . . . . . .  21
     7.5.  Control Loops (*) . . . . . . . . . . . . . . . . . . . .  21
     7.6.  APIs (*)  . . . . . . . . . . . . . . . . . . . . . . . .  22
     7.7.  Data Model (*)  . . . . . . . . . . . . . . . . . . . . .  23
   8.  Coordination Between Autonomic Functions (*)  . . . . . . . .  23



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     8.1.  The Coordination Problem (*)  . . . . . . . . . . . . . .  23
     8.2.  A Coordination Functional Block (*) . . . . . . . . . . .  25
   9.  Security Considerations . . . . . . . . . . . . . . . . . . .  25
     9.1.  Protection Against Outsider Attacks . . . . . . . . . . .  25
     9.2.  Risk of Insider Attacks . . . . . . . . . . . . . . . . .  26
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  27
   11. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  27
   12. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  27
   13. References  . . . . . . . . . . . . . . . . . . . . . . . . .  28
     13.1.  Normative References . . . . . . . . . . . . . . . . . .  28
     13.2.  Informative References . . . . . . . . . . . . . . . . .  28
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  29

1.  Introduction

   The document "Autonomic Networking - Definitions and Design Goals"
   [RFC7575] explains the fundamental concepts behind Autonomic
   Networking, and defines the relevant terms in this space, as well as
   a high level reference model.  [RFC7576] provides a gap analysis
   between traditional and autonomic approaches.

   This document defines this reference model with more detail, to allow
   for functional and protocol specifications to be developed in an
   architecturally consistent, non-overlapping manner.

   As discussed in [RFC7575], the goal of this work is not to focus
   exclusively on fully autonomic nodes or networks.  In reality, most
   networks will run with some autonomic functions, while the rest of
   the network is traditionally managed.  This reference model allows
   for this hybrid approach.

   For example, it is possible in an existing, non-autonomic network to
   enrol devices in a traditional way, to bring up a trust
   infrastructure with certificates.  This trust infrastructure could
   then be used to automatically bring up an Autonomic Control Plane
   (ACP), and run traditional network operations over the secure and
   self-healing ACP.  See [I-D.ietf-anima-stable-connectivity] for a
   description of this use case.

   The scope of this model is therefore limited to networks that are to
   some extent managed by skilled human operators, loosely referred to
   as "professionally managed" networks.  Unmanaged networks raise
   additional security and trust issues that this model does not cover.

   This document describes a first, simple, implementable phase of an
   Autonomic Networking solution.  It is expected that the experience
   from this phase will be used in defining updated and extended
   specifications over time.  Some topics are considered architecturally



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   in this document, but are not yet reflected in the implementation
   specifications.  They are marked with an (*).

2.  The Network View

   This section describes the various elements in a network with
   autonomic functions, and how these entities work together, on a high
   level.  Subsequent sections explain the detailed inside view for each
   of the autonomic network elements, as well as the network functions
   (or interfaces) between those elements.

   Figure 1 shows the high level view of an Autonomic Network.  It
   consists of a number of autonomic nodes, which interact directly with
   each other.  Those autonomic nodes provide a common set of
   capabilities across the network, called the "Autonomic Networking
   Infrastructure" (ANI).  The ANI provides functions like naming,
   addressing, negotiation, synchronization, discovery and messaging.

   Autonomic functions typically span several, possibly all nodes in the
   network.  The atomic entities of an autonomic function are called the
   "Autonomic Service Agents" (ASA), which are instantiated on nodes.

   +- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +
   :            :       Autonomic Function 1        :                 :
   : ASA 1      :      ASA 1      :      ASA 1      :          ASA 1  :
   +- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +
                :                 :                 :
                :   +- - - - - - - - - - - - - - +  :
                :   :   Autonomic Function 2     :  :
                :   :  ASA 2      :      ASA 2   :  :
                :   +- - - - - - - - - - - - - - +  :
                :                 :                 :
   +- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +
   :                Autonomic Networking Infrastructure               :
   +- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +
   +--------+   :    +--------+   :    +--------+   :        +--------+
   | Node 1 |--------| Node 2 |--------| Node 3 |----...-----| Node n |
   +--------+   :    +--------+   :    +--------+   :        +--------+

             Figure 1: High level view of an Autonomic Network

   In a horizontal view, autonomic functions span across the network, as
   well as the Autonomic Networking Infrastructure.  In a vertical view,
   a node always implements the ANI, plus it may have one or several
   Autonomic Service Agents.  ASAs may be standalone, or use other ASAs
   in a hierarchical way.





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   The Autonomic Networking Infrastructure (ANI) therefore is the
   foundation for autonomic functions.

3.  The Autonomic Network Element

   This section explains the general architecture of an Autonomic
   Network Element (Section 3.1), how it tracks its surrounding
   environment in an Adjacency Table (Section 3.2), and the state
   machine which defines the behaviour of the network element
   (Section 3.3), based on that adjacency table.

3.1.  Architecture

   This section describes an autonomic network element and its internal
   architecture.  The reference model explained in the document
   "Autonomic Networking - Definitions and Design Goals" [RFC7575] shows
   the sources of information that an autonomic service agent can
   leverage: Self-knowledge, network knowledge (through discovery),
   Intent (see Section 7.2), and feedback loops.  There are two levels
   inside an autonomic node: the level of Autonomic Service Agents, and
   the level of the Autonomic Networking Infrastructure, with the former
   using the services of the latter.  Figure 2 illustrates this concept.

   +------------------------------------------------------------+
   |                                                            |
   | +-----------+        +------------+        +------------+  |
   | | Autonomic |        | Autonomic  |        | Autonomic  |  |
   | | Service   |        | Service    |        | Service    |  |
   | | Agent 1   |        | Agent 2    |        | Agent 3    |  |
   | +-----------+        +------------+        +------------+  |
   |       ^                    ^                     ^         |
   | -  -  | -  - API level -  -| -  -  -  -  -  -  - |-  -  -  |
   |       V                    V                     V         |
   |------------------------------------------------------------|
   | Autonomic Networking Infrastructure                        |
   |    - Data structures (ex: certificates, peer information)  |
   |    - Generalized Autonomic Control Plane (GACP)            |
   |    - Autonomic Node Addressing and naming                  |
   |    - Discovery, negotiation and synchronisation functions  |
   |    - Distribution of Intent and other information          |
   |    - Aggregated reporting and feedback loops               |
   |    - Routing                                               |
   |------------------------------------------------------------|
   |             Basic Operating System Functions               |
   +------------------------------------------------------------+

                   Figure 2: Model of an autonomic node




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   The Autonomic Networking Infrastructure (lower part of Figure 2)
   contains node specific data structures, for example trust information
   about itself and its peers, as well as a generic set of functions,
   independent of a particular usage.  This infrastructure should be
   generic, and support a variety of Autonomic Service Agents (upper
   part of Figure 2).  It contains addressing and naming of autonomic
   nodes, discovery, negotiation and synchronisation functions,
   distribution of information, reporting and feedback loops, as well as
   routing inside the Autonomic Control Plane.

   The Generalized Autonomic Control Plane (GACP) is the summary of all
   interactions of the Autonomic Networking Infrastructure with other
   nodes and services.  A specific implementation of the GACP is
   referred to here as the Autonomic Control Plane (ACP), and described
   in [I-D.ietf-anima-autonomic-control-plane].

   The use cases of "Autonomics" such as self-management, self-
   optimisation, etc, are implemented as Autonomic Service Agents.  They
   use the services and data structures of the underlying Autonomic
   Networking Infrastructure, which should be self-managing.

   The "Basic Operating System Functions" include the "normal OS",
   including the network stack, security functions, etc.

   Full AN nodes have the full Autonomic Networking Infrastructure, with
   the full functionality described in this document.  At a later stage
   ANIMA may define a scope for constrained nodes with a reduced ANI and
   well-defined minimal functionality.  They are currently out of scope.

3.2.  The Adjacency Table

   Autonomic Networking is based on direct interactions between devices
   of a domain.  The Autonomic Control Plane (ACP) is normally
   constructed on a hop-by-hop basis.  Therefore, many interactions in
   the ANI are based on the ANI adjacency table.  There are interactions
   that provide input into the adjacency table, and other interactions
   that leverage the information contained in it.

   The ANI adjacency table contains information about adjacent autonomic
   nodes, at a minimum: node-ID, IP address in data plane, IP address in
   ACP, domain, certificate.  An autonomic node maintains this adjacency
   table up to date.  The adjacency table only contains information
   about other nodes that are capable of Autonomic Networking; non-
   autonomic nodes are normally not tracked here.  However, the
   information is tracked independently of the status of the peer nodes;
   specifically, it contains information about non-enrolled nodes, nodes
   of the same and other domains.  The adjacency table may contain




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   information about the validity and trust level of the adjacent
   autonomic nodes.

   The adjacency table is fed by the following inputs:

   o  Link local discovery: This interaction happens in the data plane,
      using IPv6 link local addressing only, because this addressing
      type is itself autonomic.  This way the nodes learns about all
      autonomic nodes around itself.  The related standards track
      documents ([I-D.ietf-anima-grasp],
      [I-D.ietf-anima-bootstrapping-keyinfra],
      [I-D.ietf-anima-autonomic-control-plane]) describe in detail how
      link local discovery is used.

   o  Vendor re-direct: A new device may receive information on where
      its home network is through a vendor based Manufacturer Authorized
      Signing Authority (MASA, see Section 5.3) re-direct; this is
      typically a routable address.

   o  Non-autonomic input: A node may be configured manually with an
      autonomic peer; it could learn about autonomic nodes through DHCP
      options, DNS, and other non-autonomic mechanisms.  Generally such
      non-autonomic mechansims require some administrator intervention.
      The key purpose is to by-pass a non-autonomic device or network.
      As this pertains to new devices, it is covered in appendix A and B
      of [I-D.ietf-anima-bootstrapping-keyinfra].

   The adjacency table is defining the behaviour of an autonomic node:

   o  If the node has not bootstrapped into a domain (i.e., doesn't have
      a domain certificate), it rotates through all nodes in the
      adjacency table that claim to have a domain, and will attempt
      bootstrapping through them, one by one.  One possible response is
      a re-direct via a vendor MASA, which will be entered into the
      adjacency table (see second bullet above).  See
      [I-D.ietf-anima-bootstrapping-keyinfra] for details.

   o  If the adjacent node has the same domain, it will authenticate
      that adjacent node and, if successful, establish the Autonomic
      Control Plane (ACP).  See
      [I-D.ietf-anima-autonomic-control-plane].

   o  Once the node is part of the ACP of a domain, it will use GRASP
      [I-D.ietf-anima-grasp] to find Registrar(s) of its domain and
      potentially other services.

   o  If the node is part of an ACP and has discovered at least one
      Registrar in its domain via GRASP, it will start the "join



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      assistant" ASA, and act as a join assistant for neighboring nodes
      that need to be bootstrapped.  See Section 6.3.1.2 for details.

   o  Other behaviours are possible, for example establishing the ACP
      also with devices of a sub-domain, to other domains, etc.  Those
      will likely be controlled by Intent.  They are outside scope for
      the moment.  Note that Intent is distributed through the ACP;
      therefore, a node can only adapt Intent driven behaviour once it
      has joined the ACP.  At the moment, ANIMA does not consider
      providing Intent outside the ACP; this can be considered later.

   Once a node has joined the ACP, it will also learn the ACP addresses
   of its adjacent nodes, and add them to the adjacency table, to allow
   for communication inside the ACP.  Further autonomic domain
   interactions will now happen inside the ACP.  At this moment, only
   negotiation / synchronization via GRASP [I-D.ietf-anima-grasp] is
   being defined.  (Note that GRASP runs in the data plane, as an input
   in building the adjacency table, as well as inside the ACP.)

   Autonomic Functions consist of Autonomic Service Agents (ASAs).  They
   run logically above the AN Infrastructure, and may use the adjacency
   table, the ACP, negotiation and synchronization through GRASP in the
   ACP, Intent and other functions of the ANI.  Since the ANI only
   provides autonomic interactions within a domain, autonomic functions
   can also use any other context on a node, specifically the global
   data plane.

3.3.  State Machine

   Autonomic Networking applies during the full life-cycle of a node.
   This section describes a state machine of an autonomic node,
   throughout its life.

   A device is normally expected to store its domain specific identity,
   the LDevID (see Section 5.2), in persistent storage, to be available
   after a powercycle event.  For device types that cannot store the
   LDevID in persistent storage, a powercycle event is effectively
   equivalent to a factory reset.

3.3.1.  State 1: Factory Default

   An autonomic node leaves the factory in this state.  In this state,
   the node has no domain specific configuration, specifically no
   LDevID, and could be used in any particular target network.  It does
   however have a vendor/manufacturer specific ID, the IDevID [IDevID].
   Nodes without IDevID cannot be autonomically and securely enrolled
   into a domain; they require manual pre-staging, in which case the
   pre-staging takes them directly to state 2.



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   Transitions:

   o  Bootstrap event: The device enrols into a domain; as part of this
      process it receives a domain identity (LDevID).  If enrollment is
      successful, the next state is state 2.  See
      [I-D.ietf-anima-bootstrapping-keyinfra] Section 3 for details on
      enrollment.

   o  Powercycle event: The device loses all state tables.  It remains
      in state: 1.

3.3.2.  State 2: Enrolled

   An autonomic node is in the state "enrolled" if it has a domain
   identity (LDevID), and has currently no ACP channel up.  It may have
   further configuration or state, for example if it had been in state 3
   before, but lost all its ACP channels.  The LDevID can only be
   removed from a device through a factory reset, which also removes all
   other state from the device.  This ensures that a device has no stale
   domain specific state when entering the "enrolled" state from state
   1.

   Transitions:

   o  Joining ACP: The device establishes an ACP channel to an adjacent
      device.  See [I-D.ietf-anima-autonomic-control-plane] for details.
      Next state: 3.

   o  Factory reset: A factory reset removes all configuration and the
      domain identity (LDevID) from the device.  Next state: 1.

   o  Powercycle event: The device loses all state tables, but not its
      domain identity (LDevID). it remains in state: 2.

3.3.3.  State 3: In ACP

   In this state, the autonomic node has at least one ACP channel to
   another device.  It can participate in further autonomic
   transactions, such as starting autonomic service agents.  For example
   it must now enable the join assistant ASA, to help other devices to
   join the domain.  Other conditions may apply to such interactions,
   for example to serve as a join assistant, the device must first
   discover a bootstrap Registrar.

   Transitions:

   o  Leaving ACP: The device drops the last (or only) ACP channel to an
      adjacent device.  Next state: 2.



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   o  Factory reset: A factory reset removes all configuration and the
      domain identity (LDevID) from the device.  Next state: 1.

   o  Powercycle event: The device loses all state tables, but not its
      domain identity (LDevID).  Next state: 2.

4.  The Autonomic Networking Infrastructure

   The Autonomic Networking Infrastructure provides a layer of common
   functionality across an Autonomic Network.  It provides the
   elementary functions and services, as well as extensions.  An
   Autonomic Function, comprising of Autonomic Service Agents on nodes,
   uses the functions described in this section.

4.1.  Naming

   Inside a domain, each autonomic device should be assigned a unique
   name.  The naming scheme should be consistent within a domain.  Names
   are typically assigned by a Registrar at bootstrap time and
   persistent over the lifetime of the device.  All Registrars in a
   domain must follow the same naming scheme.

   In the absence of a domain specific naming scheme, a default naming
   scheme should use the same logic as the addressing scheme discussed
   in [I-D.ietf-anima-autonomic-control-plane].  The device name is then
   composed of a Registrar ID (for example taking a MAC address of the
   Registrar) and a device number.  An example name would then look like
   this:

   0123-4567-89ab-0001

   The first three fields are the MAC address, the fourth field is the
   sequential number for the device.

4.2.  Addressing

   Autonomic Service Agents (ASAs) need to communicate with each other,
   using the autonomic addressing of the Autonomic Networking
   Infrastructure of the node they reside on.  This section describes
   the addressing approach of the Autonomic Networking Infrastructure,
   used by ASAs.

   Out of scope are addressing approaches for the data plane of the
   network, which may be configured and managed in the traditional way,
   or negotiated as a service of an ASA.  One use case for such an
   autonomic function is described in
   [I-D.ietf-anima-prefix-management].




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   Autonomic addressing is a function of the Autonomic Networking
   Infrastructure (lower part of Figure 2), specifically the Autonomic
   Control Plane.  ASAs do not have their own addresses.  They may use
   either API calls, or the autonomic addressing scheme of the Autonomic
   Networking Infrastructure.

   An autonomic addressing scheme has the following requirements:

   o  Zero-touch for simple networks: Simple networks should have
      complete self-management of addressing, and not require any
      central address management, tools, or address planning.

   o  Low-touch for complex networks: If complex networks require
      operator input for autonomic address management, it should be
      limited to high level guidance only, expressed in Intent.

   o  Flexibility: The addressing scheme must be flexible enough for
      nodes to be able to move around, for the network to grow, split
      and merge.

   o  Robustness: It should be as hard as possible for an administrator
      to negatively affect addressing (and thus connectivity) in the
      autonomic context.

   o  Stability: The addressing scheme should be as stable as possible.
      However, implementations need to be able to recover from
      unexpected address changes.

   o  Support for virtualization: Autonomic Nodes may support Autonomic
      Service Agents in different virtual machines or containers.  The
      addressing scheme should support this architecture.

   o  Simplicity: To make engineering simpler, and to give the human
      administrator an easy way to trouble-shoot autonomic functions.

   o  Scale: The proposed scheme should work in any network of any size.

   o  Upgradability: The scheme must be able to support different
      addressing concepts in the future.

   The proposed addressing scheme is described in the document "An
   Autonomic Control Plane" ([I-D.ietf-anima-autonomic-control-plane]).

4.3.  Discovery

   Traditionally, most of the information a node requires is provided
   through configuration or northbound interfaces.  An autonomic
   function should rely on such northbound interfaces minimally or not



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   at all, and therefore it needs to discover peers and other resources
   in the network.  This section describes various discovery functions
   in an autonomic network.

   Discovering nodes and their properties and capabilities: A core
   function to establish an autonomic domain is the mutual discovery of
   autonomic nodes, primarily adjacent nodes and secondarily off-link
   peers.  This may in principle either leverage existing discovery
   mechanisms, or use new mechanisms tailored to the autonomic context.
   An important point is that discovery must work in a network with no
   predefined topology, ideally no manual configuration of any kind, and
   with nodes starting up from factory condition or after any form of
   failure or sudden topology change.

   Discovering services: Network services such as AAA should also be
   discovered and not configured.  Service discovery is required for
   such tasks.  An autonomic network can either leverage existing
   service discovery functions, or use a new approach, or a mixture.

   Thus the discovery mechanism could either be fully integrated with
   autonomic signaling (next section) or could use an independent
   discovery mechanism such as DNS Service Discovery or Service Location
   Protocol.  This choice could be made independently for each Autonomic
   Service Agent, although the infrastructure might require some minimal
   lowest common denominator (e.g., for discovering the security
   bootstrap mechanism, or the source of information distribution,
   Section 4.7).

   Phase 1 of Autonomic Networking uses GRASP for discovery, described
   in [I-D.ietf-anima-grasp].

4.4.  Signaling Between Autonomic Nodes

   Autonomic nodes must communicate with each other, for example to
   negotiate and/or synchronize technical objectives (i.e., network
   parameters) of any kind and complexity.  This requires some form of
   signaling between autonomic nodes.  Autonomic nodes implementing a
   specific use case might choose their own signaling protocol, as long
   as it fits the overall security model.  However, in the general case,
   any pair of autonomic nodes might need to communicate, so there needs
   to be a generic protocol for this.  A prerequisite for this is that
   autonomic nodes can discover each other without any preconfiguration,
   as mentioned above.  To be generic, discovery and signaling must be
   able to handle any sort of technical objective, including ones that
   require complex data structures.  The document "A Generic Autonomic
   Signaling Protocol (GRASP)" [I-D.ietf-anima-grasp] describes more
   detailed requirements for discovery, negotiation and synchronization




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   in an autonomic network.  It also defines a protocol, GRASP, for this
   purpose, including an integrated but optional discovery protocol.

   GRASP is normally expected to run inside the Autonomic Control Plane
   (ACP; see Section 4.6) and to depend on the ACP for security.  It may
   run insecurely for a short time during bootstrapping.

   An autonomic node will normally run a single instance of GRASP, used
   by multiple ASAs.  However, scenarios where multiple instances of
   GRASP run in a single node, perhaps with different security
   properties, are not excluded.

4.5.  Routing

   All autonomic nodes in a domain must be able to communicate with each
   other, and later phases also with autonomic nodes outside their own
   domain.  Therefore, an Autonomic Control Plane relies on a routing
   function.  For Autonomic Networks to be interoperable, they must all
   support one common routing protocol.

   The routing protocol is defined in the ACP document
   [I-D.ietf-anima-autonomic-control-plane].

4.6.  The Autonomic Control Plane

   The "Autonomic Control Plane" carries the control protocols in an
   autonomic network.  This control plane can be either implemented in
   the global routing table of a node, such as IGPs in today's networks;
   or it can be provided as an overlay network.  The document "An
   Autonomic Control Plane" ([I-D.ietf-anima-autonomic-control-plane])
   describes the implementation details suggested here.  See
   [I-D.ietf-anima-stable-connectivity] for uses cases for the ACP.

4.7.  Information Distribution (*)

   Certain forms of information require distribution across an autonomic
   domain.  The distribution of information runs inside the Autonomic
   Control Plane.  For example, Intent is distributed across an
   autonomic domain, as explained in [RFC7575].

   Intent is the policy language of an Autonomic Network, see also
   Section 7.2.  It is a high level policy, and should change only
   infrequently (order of days).  Therefore, information such as Intent
   should be simply flooded to all nodes in an autonomic domain, and
   there is currently no perceived need to have more targeted
   distribution methods.  Intent is also expected to be monolithic, and
   flooded as a whole.  One possible method for distributing Intent, as
   well as other forms of data, is discussed in



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   [I-D.liu-anima-grasp-distribution].  Intent and information
   distribution are not part of phase 1 of ANIMA.

5.  Security and Trust Infrastructure

   An Autonomic Network is self-protecting.  All protocols are secure by
   default, without the requirement for the administrator to explicitly
   configure security, with the exception of setting up a PKI
   infrastructure.

   Autonomic nodes have direct interactions between themselves, which
   must be secured.  Since an autonomic network does not rely on
   configuration, it is not an option to configure, for example, pre-
   shared keys.  A trust infrastructure such as a PKI infrastructure
   must be in place.  This section describes the principles of this
   trust infrastructure.

   The default method to automatically bring up a trust infrastructure
   is defined in the document "Bootstrapping Key Infrastructures"
   [I-D.ietf-anima-bootstrapping-keyinfra].  The ASAs required for this
   enrollment process are described in Section 6.3.  An autonomic node
   must implement the enrollment and join assistant ASAs.  The registrar
   ASA may be implemented only on a sub-set of nodes.

5.1.  Public Key Infrastructure

   An autonomic domain uses a PKI model.  The root of trust is a
   certification authority (CA).  A registrar acts as a registration
   authority (RA).

   A minimum implementation of an autonomic domain contains one CA, one
   Registrar, and network elements.

5.2.  Domain Certificate

   Each device in an autonomic domain uses a domain certificate (LDevID)
   to prove its identity.  A new device uses its manufacturer provided
   certificate (IDevID) during bootstrap, to obtain a domain
   certificate.  [I-D.ietf-anima-bootstrapping-keyinfra] describes how a
   new device receives a domain certificate, and the certificate format.

5.3.  The MASA

   The Manufacturer Authorized Signing Authority (MASA) is a trusted
   service for bootstrapping devices.  The purpose of the MASA is to
   provide ownership tracking of devices in a domain.  The MASA provides
   audit, authorization, and ownership tokens to the registrar during
   the bootstrap process to assist in the authentication of devices



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   attempting to join an Autonomic Domain, and to allow a joining device
   to validate whether it is joining the correct domain.  The details
   for MASA service, security, and usage are defined in
   [I-D.ietf-anima-bootstrapping-keyinfra].

5.4.  Sub-Domains (*)

   By default, sub-domains are treated as different domains.  This
   implies no trust between a domain and its sub-domains, and no trust
   between sub-domains of the same domain.  Specifically, no ACP is
   built, and Intent is valid only for the domain it is defined for
   explicitly.

   In phase 2 of ANIMA, alternative trust models should be defined, for
   example to allow full or limited trust between domain and sub-domain.

5.5.  Cross-Domain Functionality (*)

   By default, different domains do not interoperate, no ACP is built
   and no trust is implied between them.

   In the future, models can be established where other domains can be
   trusted in full or for limited operations between the domains.

6.  Autonomic Service Agents (ASA)

   This section describes how autonomic services run on top of the
   Autonomic Networking Infrastructure.

6.1.  General Description of an ASA

   An Autonomic Service Agent (ASA) is defined in [RFC7575] as "An agent
   implemented on an autonomic node that implements an autonomic
   function, either in part (in the case of a distributed function) or
   whole."  Thus it 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 [I-D.ietf-anima-grasp] 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.
   ASA design guidelines are available in
   [I-D.carpenter-anima-asa-guidelines].

   Thus we can distinguish at least three classes of ASAs:

   o  Simple ASAs with a small footprint that could run anywhere.



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   o  Complex, possibly multi-threaded ASAs that have a significant
      resource requirement and will only run on selected nodes.

   o  A few 'infrastructure ASAs' that use basic ANI features in support
      of the ANI itself, which must run in all autonomic nodes.  These
      are outlined in the following sections.

   Autonomic nodes, and therefore their ASAs, know their own
   capabilities and restrictions, derived from hardware, firmware or
   pre-installed software: They are "self-aware".

   The role of an autonomic node depends on Intent and on the
   surrounding network behaviors, which may include forwarding
   behaviors, aggregation properties, topology location, bandwidth,
   tunnel or translation properties, etc.  For example, a node may
   decide to act as a backup node for a neighbor, if its capabilities
   allow it to do so.

   Following an initial discovery phase, the device properties and those
   of its neighbors are the foundation of the behavior of a specific
   device.  A device and its ASAs have no pre-configuration for the
   particular network in which they are installed.

   Since all ASAs will interact with the ANI, they will depend on
   appropriate application programming interfaces (APIs).  It is
   desirable that ASAs are portable between operating systems, so these
   APIs need to be universal.  An API for GRASP is described in
   [I-D.ietf-anima-grasp-api].

   ASAs will in general be designed and coded by experts in a particular
   technology and use case, not by experts in the ANI and its
   components.  Also, they may be coded in a variety of programming
   languages, in particular including languages that support object
   constructs as well as traditional variables and structures.  The APIs
   should be designed with these factors in mind.

   It must be possible to run ASAs as non-privileged (user space)
   processes except for those (such as the infrastructure ASAs) that
   necessarily require kernel privilege.  Also, it is highly desirable
   that ASAs can be dynamically loaded on a running node.

   Since autonomic systems must be self-repairing, it is of great
   importance that ASAs are coded using robust programming techniques.
   All run-time error conditions must be caught, leading to suitable
   recovery actions, with a complete restart of the ASA as a last
   resort.  Conditions such as discovery failures or negotiation
   failures must be treated as routine, with the ASA retrying the failed
   operation, preferably with an exponential back-off in the case of



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   persistent errors.  When multiple threads are started within an ASA,
   these threads must be monitored for failures and hangups, and
   appropriate action taken.  Attention must be given to garbage
   collection, so that ASAs never run out of resources.  There is
   assumed to be no human operator - again, in the worst case, every ASA
   must be capable of restarting itself.

   ASAs will automatically benefit from the security provided by the
   ANI, and specifically by the ACP and by GRASP.  However, beyond that,
   they are responsible for their own security, especially when
   communicating with the specific targets of their function.
   Therefore, the design of an ASA must include a security analysis
   beyond 'use ANI security.'

6.2.  ASA Life-Cycle Management

   ASAs operating on a given ANI may come from different providers and
   pursue different objectives.  Management of ASAs and its interactions
   with the ANI should follow the same operating principles, hence
   comply to a generic life-cycle management model.

   The ASA life-cycle provides standard processes to:

   o  install ASA: copy the ASA code onto the host and start it,

   o  deploy ASA: associate the ASA instance with a (some) managed
      network device(s) (or network function),

   o  control ASA execution: when and how an ASA executes its control
      loop.

   The life-cyle will cover the sequential states below: Installation,
   Deployment, Operation and the transitional states in-between.  This
   Life-Cycle will also define which interactions ASAs have with the ANI
   in between the different states.  The noticeable interactions are:

   o  Self-description of ASA instances at the end of deployment: its
      format needs to define the information required for the management
      of ASAs by ANI entities

   o  Control of ASA control-loop during the operation: a signaling has
      to carry formatted messages to control ASA execution (at least
      starting and stopping the control loop)








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6.3.  Specific ASAs for the Autonomic Network Infrastructure

   The following functions provide essential, required functionality in
   an autonomic network, and are therefore mandatory to implement on
   unconstrained autonomic nodes.  They are described here as ASAs that
   include the underlying infrastructure components, but implementation
   details might vary.

   The first three together support the trust enrollment process
   described in Section 5.  For details see
   [I-D.ietf-anima-bootstrapping-keyinfra].

6.3.1.  The enrollment ASAs

6.3.1.1.  The Pledge ASA

   This ASA includes the function of an autonomic node that bootstraps
   into the domain with the help of an join assitant ASA (see below).
   Such a node is known as a Pledge during the enrollment process.  This
   ASA must be installed by default on all nodes that require an
   autonomic zero-touch bootstrap.

6.3.1.2.  The Join Assistant ASA

   This ASA includes the function of an autonomic node that helps a non-
   enrolled, adjacent devices to enroll into the domain.  This ASA must
   be installed on all nodes, although only one join assistant needs to
   be active on a given LAN.  See also
   [I-D.ietf-anima-bootstrapping-keyinfra].

6.3.1.3.  The Join Registrar ASA

   This ASA includes the join registrar function in an autonomic
   network.  This ASA does not need to be installed on all nodes, but
   only on nodes that implement the Join Registrar function.

6.3.2.  The ACP ASA

   This ASA includes the ACP function in an autonomic network.  In
   particular it acts to discover other potential ACP nodes, and to
   support the establishment and teardown of ACP channels.  This ASA
   must be installed on all nodes.  For details see Section 4.6 and
   [I-D.ietf-anima-autonomic-control-plane].








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6.3.3.  The Information Distribution ASA (*)

   This ASA is currently out of scope in ANIMA, and provided here only
   as background information.

   This ASA includes the information distribution function in an
   autonomic network.  In particular it acts to announce the
   availability of Intent and other information to all other autonomic
   nodes.  This ASA does not need to be installed on all nodes, but only
   on nodes that implement the information distribution function.  For
   details see Section 4.7.

   Note that information distribution can be implemented as a function
   in any ASA.  See [I-D.liu-anima-grasp-distribution] for more details
   on how information is suggested to be distributed.

7.  Management and Programmability

   This section describes how an Autonomic Network is managed, and
   programmed.

7.1.  Managing a (Partially) Autonomic Network

   Autonomic management usually co-exists with traditional management
   methods in most networks.  Thus, autonomic behavior will be defined
   for individual functions in most environments.  Examples for overlap
   are:

   o  Autonomic functions can use traditional methods and protocols
      (e.g., SNMP and NETCONF) to perform management tasks, inside and
      outside the ACP;

   o  Autonomic functions can conflict with behavior enforced by the
      same traditional methods and protocols;

   o  Traditional functions can use the ACP, for example if reachability
      on the data plane is not (yet) established.

   The autonomic Intent is defined at a high level of abstraction.
   However, since it is necessary to address individual managed
   elements, autonomic management needs to communicate in lower-level
   interactions (e.g., commands and requests).  For example, it is
   expected that the configuration of such elements be performed using
   NETCONF and YANG modules as well as the monitoring be executed
   through SNMP and MIBs.

   Conflict can occur between autonomic default behavior, autonomic
   Intent, traditional management methods.  Conflict resolution is



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   achieved in autonomic management through prioritization [RFC7575].
   The rationale is that manual and node-based management have a higher
   priority over autonomic management.  Thus, the autonomic default
   behavior has the lowest priority, then comes the autonomic Intent
   (medium priority), and, finally, the highest priority is taken by
   node-specific network management methods, such as the use of command
   line interfaces.

7.2.  Intent (*)

   Intent is not covered in the current implementation specifications.
   This section is for informational purposes, for following phases of
   standardization.

   This section gives an overview of Intent, and how it is managed.
   Intent and Policy-Based Network Management (PBNM) is already
   described inside the IETF (e.g., PCIM) and in other SDOs (e.g., DMTF
   and TMF ZOOM).

   Intent can be described as an abstract, declarative, high-level
   policy used to operate an autonomic domain, such as an enterprise
   network [RFC7575].  Intent should be limited to high level guidance
   only, thus it does not directly define a policy for every network
   element separately.

   Intent can be refined to lower level policies using different
   approaches.  This is expected in order to adapt the Intent to the
   capabilities of managed devices.  Intent may contain role or function
   information, which can be translated to specific nodes [RFC7575].
   One of the possible refinements of the Intent is using Event-
   Condition-Action (ECA) rules.

   Different parameters may be configured for Intent.  These parameters
   are usually provided by the human operator.  Some of these parameters
   can influence the behavior of specific autonomic functions as well as
   the way the Intent is used to manage the autonomic domain.

   Intent is discussed in more detail in [I-D.du-anima-an-intent].
   Intent as well as other types of information are distributed via
   GRASP, see [I-D.liu-anima-grasp-distribution].

7.3.  Aggregated Reporting (*)

   Aggregated reporting is not covered in the current implementation
   specifications.  This section is for informational purposes, for
   following phases of standardization.





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   An Autonomic Network should minimize the need for human intervention.
   In terms of how the network should behave, this is done through an
   autonomic Intent provided by the human administrator.  In an
   analogous manner, the reports which describe the operational status
   of the network should aggregate the information produced in different
   network elements in order to present the effectiveness of autonomic
   Intent enforcement.  Therefore, reporting in an autonomic network
   should happen on a network-wide basis [RFC7575].

   Multiple simultaneous events can occur in an autonomic network in the
   same way they can happen in a traditional network.  However, when
   reporting to a human administrator, such events should be aggregated
   to avoid notifications about individual managed elements.  In this
   context, algorithms may be used to determine what should be reported
   (e.g., filtering) and in which way and how different events are
   related to each other.  Besides that, an event in an individual
   element can be compensated by changes in other elements to maintain a
   network-wide target which is described in the autonomic Intent.

   Reporting in an autonomic network may be at the same abstraction
   level as Intent.  In this context, the aggregated view of current
   operational status of an autonomic network can be used to switch to
   different management modes.  Despite the fact that autonomic
   management should minimize the need for user intervention, possibly
   there are some events that need to be addressed by human
   administrator actions.

7.4.  Feedback Loops to NOC (*)

   Feedback loops are required in an autonomic network to allow the
   intervention of a human administrator or central control systems,
   while maintaining a default behaviour.  Through a feedback loop an
   administrator can be prompted with a default action, and has the
   possibility to acknowledge or override the proposed default action.

7.5.  Control Loops (*)

   Control loops are not covered in the current implementation
   specifications.  This section is for informational purposes, for
   following phases of standardization.

   Control loops are used in autonomic networking to provide a generic
   mechanism to enable the Autonomic System to adapt (on its own) to
   various factors that can change the goals that the autonomic network
   is trying to achieve, or how those goals are achieved.  For example,
   as user needs, business goals, and the ANI itself changes, self-
   adaptation enables the ANI to change the services and resources it
   makes available to adapt to these changes.



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   Control loops operate to continuously observe and collect data that
   enables the autonomic management system to understand changes to the
   behavior of the system being managed, and then provide actions to
   move the state of the system being managed toward a common goal.
   Self-adaptive systems move decision-making from static, pre-defined
   commands to dynamic processes computed at runtime.

   Most autonomic systems use a closed control loop with feedback.  Such
   control loops should be able to be dynamically changed at runtime to
   adapt to changing user needs, business goals, and changes in the ANI.

7.6.  APIs (*)

   APIs are not covered in the current implementation specifications.
   This section is for informational purposes, for following phases of
   standardization.

   Most APIs are static, meaning that they are pre-defined and represent
   an invariant mechanism for operating with data.  An Autonomic Network
   should be able to use dynamic APIs in addition to static APIs.

   A dynamic API is one that retrieves data using a generic mechanism,
   and then enables the client to navigate the retrieved data and
   operate on it.  Such APIs typically use introspection and/or
   reflection.  Introspection enables software to examine the type and
   properties of an object at runtime, while reflection enables a
   program to manipulate the attributes, methods, and/or metadata of an
   object.

   APIs must be able to express and preserve the semantics of data
   models.  For example, software contracts [Meyer97] are based on the
   principle that a software-intensive system, such as an Autonomic
   Network, is a set of communicating components whose interaction is
   based on precisely-defined specifications of the mutual obligations
   that interacting components must respect.  This typically includes
   specifying:

   o  pre-conditions that must be satisfied before the method can start
      execution

   o  post-conditions that must be satisfied when the method has
      finished execution

   o  invariant attributes that must not change during the execution of
      the method






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7.7.  Data Model (*)

   Data models are not covered in the current implementation
   specifications.  This section is for informational purposes, for
   following phases of standardization.

   The following definitions are adapted from
   [I-D.ietf-supa-generic-policy-data-model]:

   An information model is a representation of concepts of interest to
   an environment in a form that is independent of data repository, data
   definition language, query language, implementation language, and
   protocol.  In contrast, a data model is a representation of concepts
   of interest to an environment in a form that is dependent on data
   repository, data definition language, query language, implementation
   language, and protocol (typically, but not necessarily, all three).

   The utility of an information model is to define objects and their
   relationships in a technology-neutral manner.  This forms a
   consensual vocabulary that the ANI and ASAs can use.  A data model is
   then a technology-specific mapping of all or part of the information
   model to be used by all or part of the system.

   A system may have multiple data models.  Operational Support Systems,
   for example, typically have multiple types of repositories, such as
   SQL and NoSQL, to take advantage of the different properties of each.
   If multiple data models are required by an Autonomic System, then an
   information model should be used to ensure that the concepts of each
   data model can be related to each other without technological bias.

   A data model is essential for certain types of functions, such as a
   Model-Reference Adaptive Control Loop (MRACL).  More generally, a
   data model can be used to define the objects, attributes, methods,
   and relationships of a software system (e.g., the ANI, an autonomic
   node, or an ASA).  A data model can be used to help design an API, as
   well as any language used to interface to the Autonomic Network.

8.  Coordination Between Autonomic Functions (*)

   Coordination between autonomic functions is not covered in the
   current implementation specifications.  This section is for
   informational purposes, for following phases of standardization.

8.1.  The Coordination Problem (*)

   Different autonomic functions may conflict in setting certain
   parameters.  For example, an energy efficiency function may want to
   shut down a redundant link, while a load balancing function would not



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   want that to happen.  The administrator must be able to understand
   and resolve such interactions, to steer autonomic network performance
   to a given (intended) operational point.

   Several interaction types may exist among autonomic functions, for
   example:

   o  Cooperation: An autonomic function can improve the behavior or
      performance of another autonomic function, such as a traffic
      forecasting function used by a traffic allocation function.

   o  Dependency: An autonomic function cannot work without another one
      being present or accessible in the autonomic network.

   o  Conflict: A metric value conflict is a conflict where one metric
      is influenced by parameters of different autonomic functions.  A
      parameter value conflict is a conflict where one parameter is
      modified by different autonomic functions.

   Solving the coordination problem beyond one-by-one cases can rapidly
   become intractable for large networks.  Specifying a common
   functional block on coordination is a first step to address the
   problem in a systemic way.  The coordination life-cycle consists in
   three states:

   o  At build-time, a "static interaction map" can be constructed on
      the relationship of functions and attributes.  This map can be
      used to (pre-)define policies and priorities on identified
      conflicts.

   o  At deploy-time, autonomic functions are not yet active/acting on
      the network.  A "dynamic interaction map" is created for each
      instance of each autonomic functions and on a per resource basis,
      including the actions performed and their relationships.  This map
      provides the basis to identify conflicts that will happen at run-
      time, categorize them and plan for the appropriate coordination
      strategies/mechanisms.

   o  At run-time, when conflicts happen, arbitration is driven by the
      coordination strategies.  Also new dependencies can be observed
      and inferred, resulting in an update of the dynamic interaction
      map and adaptation of the coordination strategies and mechanisms.

   Multiple coordination strategies and mechanisms exist and can be
   devised.  The set ranges from basic approaches such as random process
   or token-based process, to approaches based on time separation and
   hierarchical optimization, to more complex approaches such as multi-




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   objective optimization, and other control theory approaches and
   algorithms family.

8.2.  A Coordination Functional Block (*)

   A common coordination functional block is a desirable component of
   the ANIMA reference model.  It provides a means to ensure network
   properties and predictable performance or behavior such as stability,
   and convergence, in the presence of several interacting autonomic
   functions.

   A common coordination function requires:

   o  A common description of autonomic functions, their attributes and
      life-cycle.

   o  A common representation of information and knowledge (e.g.,
      interaction maps).

   o  A common "control/command" interface between the coordination
      "agent" and the autonomic functions.

   Guidelines, recommendations or BCPs can also be provided for aspects
   pertaining to the coordination strategies and mechanisms.

9.  Security Considerations

   In this section we distinguish outsider and insider attacks.  In an
   outsider attack all network elements and protocols are securely
   managed and operating, and an outside attacker can sniff packets in
   transit, inject and replay packets.  In an insider attack, the
   attacker has access to an autonomic node or other means (e.g. remote
   code execution in the node by exploiting ACP-independent
   vulnerabilities in the node platform) to produce arbitrary payloads
   on the protected ACP channels.

   If a system has vulnerabilities in the implementation or operation
   (configuration), an outside attacker can exploit such vulnerabilies
   to become an insider attacker.

9.1.  Protection Against Outsider Attacks

   Here, we assume that all systems involved in an autonomic network are
   secured and operated according to best current practices.  These
   protection methods comprise traditional security implementation and
   operation methods (such as code security, strong randomization
   algorithms, strong passwords, etc.) as well as mechanisms specific to
   an autonomic network (such as a secured MASA service).



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   Traditional security methods for both implementation and operation
   are outside scope for this document.

   AN specific protocols and methods must also follow traditional
   security methods, in that all packets that can be sniffed or injected
   by an outside attacker are:

   o  protected against modification.

   o  authenticated.

   o  protected against replay attacks.

   o  encrypted.

   o  and that the AN protocols are robust against packet drops and man-
      in-the-middle attacks.

   How these requirements are met is covered in the AN standards track
   documents that define the methods used, specifically
   [I-D.ietf-anima-bootstrapping-keyinfra], [I-D.ietf-anima-grasp], and
   [I-D.ietf-anima-autonomic-control-plane].

   Most AN messages run inside the cryptographically protected ACP.  The
   unprotected AN messages outside the ACP are limited to a simple
   discovery method, defined in Section 2.5.2 of [I-D.ietf-anima-grasp]:
   The "Discovery Unsolicited Link-Local (DULL)" message, with detailed
   rules on its usage.

   If AN messages can be observed by a third party, they might reveal
   valuable information about network configuration, security
   precautions in use, individual users, and their traffic patterns.  If
   encrypted, AN messages might still reveal some information via
   traffic analysis, but this would be quite limited (for example, this
   would be highly unlikely to reveal any specific information about
   user traffic).

9.2.  Risk of Insider Attacks

   An autonomic network consists of autonomic devices that form a
   distributed self-managing system.  Devices within a domain share a
   common trust anchor and thus implicitly trust each other.  This means
   that any device inside a trust domain can by default use all
   distributed functions in the entire autonomic domain in a malicious
   way.






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   If an autonomic node or protocol has vulnerabilities or is not
   securely operated, an outside attacker has the following generic ways
   to take control of an autonomic network:

   o  Introducing a fake device into the trust domain, by subverting the
      authentication methods.  This depends on the correct
      specification, implementation and operation of the AN protocols.

   o  Subverting a device which is already part of a trust domain, and
      modifying its behavior.  This threat is not specific to the
      solution discussed in this document, and applies to all network
      solutions.

   o  Exploiting potentially yet unknown protocol vulnerabilities in the
      AN or other protocols.  Also this is a generic threat that applies
      to all network solutions.

   The above threats are in principle comparable to other solutions: In
   the presence of design, implementation or operational errors,
   security is no longer guaranteed.  However, the distributed nature of
   AN, specifically the Autonomic Control Plane, increases the threat
   surface significantly.  For example, a compromised device may have
   full IP reachability to all other devices inside the ACP, and can use
   all AN methods and protocols.

   For the next phase of the ANIMA work it is therefore recommended to
   introduce a sub-domain security model, to reduce the attack surface
   and not expose a full domain to a potential intruder.  Furthermore,
   additional security mechanisms on the ASA level should be considered
   for high-risk autonomic functions.

10.  IANA Considerations

   This document requests no action by IANA.

11.  Acknowledgements

   Many people have provided feedback and input to this document: Sheng
   Jiang, Roberta Maglione, Jonathan Hansford, Jason Coleman, Artur
   Hecker.  Useful reviews were made by Joel Halpern, Radia Perlman and
   Tianran Zhou.

12.  Contributors

   Significant contributions to this document have been made by John
   Strassner and Bing Liu from Huawei, and Pierre Peloso from Nokia.





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13.  References

13.1.  Normative References

   [I-D.ietf-anima-autonomic-control-plane]
              Eckert, T., Behringer, M., and S. Bjarnason, "An Autonomic
              Control Plane (ACP)", draft-ietf-anima-autonomic-control-
              plane-18 (work in progress), August 2018.

   [I-D.ietf-anima-bootstrapping-keyinfra]
              Pritikin, M., Richardson, M., Behringer, M., Bjarnason,
              S., and K. Watsen, "Bootstrapping Remote Secure Key
              Infrastructures (BRSKI)", draft-ietf-anima-bootstrapping-
              keyinfra-16 (work in progress), June 2018.

   [I-D.ietf-anima-grasp]
              Bormann, C., Carpenter, B., and B. Liu, "A Generic
              Autonomic Signaling Protocol (GRASP)", draft-ietf-anima-
              grasp-15 (work in progress), July 2017.

13.2.  Informative References

   [I-D.carpenter-anima-asa-guidelines]
              Carpenter, B., Ciavaglia, L., Jiang, S., and P. Pierre,
              "Guidelines for Autonomic Service Agents", draft-
              carpenter-anima-asa-guidelines-05 (work in progress), June
              2018.

   [I-D.du-anima-an-intent]
              Du, Z., Jiang, S., Nobre, J., Ciavaglia, L., and M.
              Behringer, "ANIMA Intent Policy and Format", draft-du-
              anima-an-intent-05 (work in progress), February 2017.

   [I-D.ietf-anima-grasp-api]
              Carpenter, B., Liu, B., Wang, W., and X. Gong, "Generic
              Autonomic Signaling Protocol Application Program Interface
              (GRASP API)", draft-ietf-anima-grasp-api-02 (work in
              progress), June 2018.

   [I-D.ietf-anima-prefix-management]
              Jiang, S., Du, Z., Carpenter, B., and Q. Sun, "Autonomic
              IPv6 Edge Prefix Management in Large-scale Networks",
              draft-ietf-anima-prefix-management-07 (work in progress),
              December 2017.







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   [I-D.ietf-anima-stable-connectivity]
              Eckert, T. and M. Behringer, "Using Autonomic Control
              Plane for Stable Connectivity of Network OAM", draft-ietf-
              anima-stable-connectivity-10 (work in progress), February
              2018.

   [I-D.ietf-supa-generic-policy-data-model]
              Halpern, J. and J. Strassner, "Generic Policy Data Model
              for Simplified Use of Policy Abstractions (SUPA)", draft-
              ietf-supa-generic-policy-data-model-04 (work in progress),
              June 2017.

   [I-D.liu-anima-grasp-distribution]
              Liu, B., Jiang, S., Xiao, X., Hecker, A., and Z.
              Despotovic, "Information Distribution in Autonomic
              Networking", draft-liu-anima-grasp-distribution-06 (work
              in progress), July 2018.

   [IDevID]   IEEE Standard, "IEEE 802.1AR Secure Device Identifier",
              December 2009, <http://standards.ieee.org/findstds/
              standard/802.1AR-2009.html>.

   [Meyer97]  Meyer, B., "Object-Oriented Software Construction (2nd
              edition)", Prentice-Hall, ISBN 978-0136291558, 1997.

   [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,
              <https://www.rfc-editor.org/info/rfc7575>.

   [RFC7576]  Jiang, S., Carpenter, B., and M. Behringer, "General Gap
              Analysis for Autonomic Networking", RFC 7576,
              DOI 10.17487/RFC7576, June 2015,
              <https://www.rfc-editor.org/info/rfc7576>.

Authors' Addresses

   Michael H. Behringer (editor)

   Email: Michael.H.Behringer@gmail.com










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

   Email: brian.e.carpenter@gmail.com


   Toerless Eckert
   Futurewei Technologies Inc.
   2330 Central Expy
   Santa Clara  95050
   USA

   Email: tte@cs.fau.de


   Laurent Ciavaglia
   Nokia
   Villarceaux
   Nozay  91460
   FR

   Email: laurent.ciavaglia@nokia.com


   Jeferson Campos Nobre
   University of Vale do Rio dos Sinos
   Av. Unisinos, 950
   Sao Leopoldo  91501-970
   Brazil

   Email: jcnobre@unisinos.br
















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