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Versions: 00 draft-irtf-nmrg-autonomic-network-definitions

Network Working Group                                       M. Behringer
Internet-Draft                                               M. Pritikin
Intended status: Informational                              S. Bjarnason
Expires: June 23, 2014                                          A. Clemm
                                                           Cisco Systems
                                                            B. Carpenter
                                                       Univ. of Auckland
                                                                S. Jiang
                                            Huawei Technologies Co., Ltd
                                                            L. Ciavaglia
                                                          Alcatel-Lucent
                                                       December 20, 2013


          Autonomic Networking - Definitions and Design Goals
       draft-nmrg-autonomic-network-definitions-and-goals-00.txt

Abstract

   Autonomic systems were first described in 2001.  The fundamental goal
   is self-management, including self-configuration, self-optimization,
   self-healing and self-protection.

   This document applies the concepts of autonomic systems to a network,
   and describes the definitions and design goals of Autonomic
   Networking.  The goal is a network where nodes have minimal
   dependencies on human administrators or centralized management
   systems.

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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   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on June 23, 2014.






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Copyright Notice

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   described in the Simplified BSD License.

Table of Contents

   1.  Introduction to Autonomic Networking  . . . . . . . . . . . .   2
   2.  Definitions . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Design Goals  . . . . . . . . . . . . . . . . . . . . . . . .   4
     3.1.  Self-Management . . . . . . . . . . . . . . . . . . . . .   4
     3.2.  By Default Secure . . . . . . . . . . . . . . . . . . . .   5
     3.3.  Decentralisation and Distribution . . . . . . . . . . . .   5
     3.4.  Simplification of the Northbound Interfaces . . . . . . .   5
     3.5.  Abstraction . . . . . . . . . . . . . . . . . . . . . . .   6
     3.6.  Autonomic Reporting . . . . . . . . . . . . . . . . . . .   6
     3.7.  Modularity  . . . . . . . . . . . . . . . . . . . . . . .   6
     3.8.  Independence of Function and Layer  . . . . . . . . . . .   7
     3.9.  Full Life Cycle Support . . . . . . . . . . . . . . . . .   7
   4.  Non Design Goals  . . . . . . . . . . . . . . . . . . . . . .   7
     4.1.  Eliminate human operators . . . . . . . . . . . . . . . .   8
     4.2.  Eliminate emergency fixes . . . . . . . . . . . . . . . .   8
     4.3.  Eliminate management control and central policy . . . . .   8
     4.4.  Eliminate existing configuration tools  . . . . . . . . .   8
     4.5.  Eliminate existing network management systems . . . . . .   8
   5.  Guidelines for Case Studies . . . . . . . . . . . . . . . . .   9
   6.  An Autonomic Reference Model  . . . . . . . . . . . . . . . .   9
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .  10
   8.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  10
   9.  Informative References  . . . . . . . . . . . . . . . . . . .  10
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  11

1.  Introduction to Autonomic Networking

   Autonomic systems were first described in a manifesto by IBM in 2001
   [Kephart].  The fundamental concept involves eliminating external
   systems from a system's control loops and closing of control loops
   within the autonomic system itself, with the goal of providing the



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   autonomic system with self-management capabilities, including self-
   configuration, self-optimization, self-healing and self-protection.

   IP networking was initially designed with similar properties in mind.
   An IP network should be distributed and redundant to withstand
   outages in any part of the network.  A routing protocol such as OSPF
   or ISIS exhibits properties of self-management, and can thus be
   considered autonomic in the definition of this document.

   However, as IP networking evolved, the ever increasing intelligence
   of network element was often not put into protocols to follow this
   paradigm, but into configuration.  This configuration made network
   elements highly dependent on some process that manages them, either a
   human, or a network management system.

   Autonomic Networking aims at putting the intelligence of today's
   operations back into algorithms at the node level, to minimize
   dependency on human administrators and central management systems.
   Some information an autonomic node requires however cannot be
   discovered; where input from some central intelligence is required,
   it is provided in a highly abstract, network wide form.

   This document provides the definitions and gesign goals for Autonomic
   Networking.

2.  Definitions

   Autonomic: Self-managing (self-configuring, self-protecting, self-
   healing and self-optimizing); however, allowing high-level guidance
   by a central entity, through intent.

   Intent: An abstract, high level policy used to operate the network
   autonomically.  Its scope is an autonomic domain, such as an
   enterprise network.  It does not contain configuration or information
   for a specific node.  It may contain information pertaining to nodes
   with a specific role.

   Autonomic Domain: A collection of autonomic nodes that instantiate
   the same intent.

   Autonomic Function: A function which requires no configuration, and
   can derive all required information either through self-knowledge,
   discovery or through intent.

   Autonomic Service Agent: An agent implemented on an autonomic node
   which implements an autonomic function, either in part (in the case
   of a distributed function) or whole.




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   Autonomic Node: A node which employs autonomic functions.  It may
   operate on any layer of the networking stack.  Examples are routers,
   switches, personal computers, call managers, etc.

   Fully Autonomic Node: A node which employs exclusively autonomic
   functions.  It requires no configuration.

   Autonomic Network: A network containing autonomic nodes.

   Fully Autonomic Network: A network consisting of exclusively fully
   autonomic nodes.

3.  Design Goals

   This section explains the high level goals of Autonomic Networking,
   independent of any specific solutions.

3.1.  Self-Management

   The original design goals of autonomic systems as described in
   [Kephart] also apply to Autonomic Networks.  The over-arching goal is
   self-management, which is comprised of several self-* properties.
   The most commonly cited are:

   o  Self-configuration: The nodes do not require to be configured, but
      they configure themselves, based on self-knowledge, discovery, and
      intent.  Discovery is the default way for a node to receive the
      information it needs to operate.

   o  Self-healing: The nodes adapt on their own to changes in the
      environment, and heal problems automatically.

   o  Self-optimising: The nodes automatically determine ways to
      optimise their behaviour.

   o  Self-protection: The nodes automatically secure themselves against
      potential attacks.

   Almost any network can be described as "self-managing", as long as
   the definition of "self" is large enough.  For example, to a
   residential user, the service provider network she connects to could
   be considered "autonomic", because the user only specifies a very
   high level policy such as "Internet access" and is not exposed to any
   internals of the network.

   For the work in the IETF and IRTF we define the "self" properties on
   the node level.  It is the design goal to make network nodes self-
   managing, in other words, minimally dependent on management systems



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   or controllers, as well as human operators.  Self-managing nodes
   might need to exchange information with other nodes in order to
   achieve the required goals.

3.2.  By Default Secure

   All autonomic interactions should be by default secure.  This
   requires that any member of an autonomic domain can assert its
   membership using a domain identity, for example a certificate issued
   by a domain certification authority.  This domain identity is used
   for nodes to learn about their neighbouring nodes, to determine the
   boundaries of the domain, and to cryptographically secure
   interactions within the domain.  Nodes from different domains can
   also mutually verify their identity and secure interactions as long
   as they have a common trust anchor.

   A strong, cryptographically verifiable domain identity is a
   fundamental cornerstone in autonomic networking.  It can be leveraged
   to secure all communications, and allows thus automatic security
   without traditional configuration, for example pre-shared keys.

   Autonomic nodes must be able to adapt their behaviour depending on
   the domain of the node they are interacting with.

3.3.  Decentralisation and Distribution

   The goal of Autonomic Networking is to minimise dependencies on
   central elements; therefore, de-centralisation and distribution are
   fundamental to the concept.  If a problem can be solved in a
   distributed manner, it should not be centralised.

   In certain cases it is today operationally preferable to keep a
   central repository of information, for example a user database on a
   AAA server.  An autonomic network must also be able to use such
   central systems, in order to be deployable.  However, it is possible
   to distribute such databases as well, and such efforts should be at
   least considered.

3.4.  Simplification of the Northbound Interfaces

   Even in a decentralised solution, certain information flows with
   central entities are required.  Examples are the definition of intent
   or high level service definitions, as well as network status requests
   and aggregated reporting.

   Therefore, also elements in an autonomic network require a northbound
   interface.  However, the design goal is to maintain this interface as
   simple and high level as possible.



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3.5.  Abstraction

   An administrator or autonomic management system interacts with an
   autonomic network on a high level of abstraction.  Intent is defined
   at a level of abstraction that is much higher than that of typical
   configuration parameters, for example, "optimize my network for
   energy efficiency".  Intent must not be used to convey low-level
   commands or concepts, since those are on a different abstraction
   level.  The administrator should not even be exposed to the version
   of the IP protocol running in the network.

   Also on the reporting and feedback side an autonomic network
   abstracts information and provides high-level messages such as "the
   link between node X and Y is down".

3.6.  Autonomic Reporting

   An autonomic network, while minimizing the need for user
   intervention, still needs to provide users with visibility like in
   traditional networks.  However, in an autonomic network reporting
   should happen on a network wide basis.  Information about the network
   should be collected and aggregated by the network itself, presented
   in consolidated fashion to the administrator.

   The layers of abstraction that are provided via intent need to be
   supported for reporting functions as well, in order to give users an
   indication about the effectiveness of their intent.  For example, in
   order to assess how effective the network performs with regards to
   the intent "optimize my network for energy efficiency", the network
   should provide aggregate information about the number of ports that
   were able to be shut down while validating current service levels are
   on aggregate still met.

   Autonomic network events should concern the autonomic network as a
   whole, not individual systems in isolation.  For example, the same
   failure symptom should not be reported from every system that
   observes it, but only once for the autonomic network as a whole.
   Ultimately, the autonomic network should support exception based
   management, in which only events that truly require user attention
   are actually notified.  This requires capabilities that allow systems
   within the network to compare information and apply special
   algorithms to determine what should be reported.

3.7.  Modularity

   It is unrealistic to expect a fully autonomic network in complex
   environments for many years to come.  While simple networks may




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   become autonomic in one single step, a phased approach is required
   for most of today's networks.

   Autonomic functions can be implemented in a modular way.  For
   example, the internal routing algorithm in many networks today is
   already mostly autonomic.  Other modules can be made autonomic step
   by step.

3.8.  Independence of Function and Layer

   Today's autonomic functions may reside on any layer in the networking
   stack.  For example, layer 2 switching today is already relatively
   autonomic in many environments; routing functions can be autonomic.
   "Autonomic" in the context of this framework is a property of a node.
   This node can be a switch, router, server, or call manager.
   Autonomic functionality is independent of the function of a node.
   Even application layer functionality such as unified communications
   can be autonomic.

   An Autonomic Network requires an overall control plane for autonomic
   nodes to communicate.  As in general IP networking, IP is the layer
   that binds all those elements together; autonomic functions in the
   context of this framework should therefore operate at the IP layer.
   This concerns neighbour discovery protocols and other autonomic
   control plane functions.

3.9.  Full Life Cycle Support

   An autonomic node does not depend on external input to operate; it
   needs to understand its current situation and surrounding, and
   operate according to its current state.  Therefore, an autonomic node
   must understand its full life cycle, from first manufacturing testing
   through deployment, testing, troubleshooting, up to decommissioning.

   The state of the life-cycle of an autonomic node is reflected in a
   state model.  The behaviour of an autonomic node may be different for
   different deployment states.

4.  Non Design Goals

   This section identifies various items which are explicitly not design
   goals for autonomic networks, which are mentioned to avoid
   misunderstandings of the general intention.








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4.1.  Eliminate human operators

   The problem targeted by autonomic networking is the error-prone and
   hard to scale model of individual configuration of network elements,
   traditionally by manual commands but today mainly by scripting and/or
   configuration management databases.  This does not, however, imply
   the elimination of skilled human operators, who will still be needed
   for oversight, policy management, diagnosis, reaction to help desk
   tickets, etc. etc.  The main impact on operators should be less
   tedious detailed work and more high-level work.  (They should become
   more like doctors and nurses than hospital orderlies.)

4.2.  Eliminate emergency fixes

   However good the autonomous mechanisms, sometimes there will be fault
   conditions etc. that they cannot deal with correctly.  At this point
   skilled operator interventions will be needed to correct or work
   around the problem.  Hopefully this can be done by high-level
   mechanisms (adapting the policy database in some way) but in some
   cases direct intervention at device level may be unavoidable.  This
   is obviously the case for hardware failures, even if the autonomic
   network has bypassed the fault for the time being.  Truck rolls will
   not be eliminated when faulty equipment needs to be replaced.
   However, this may be less urgent if the autonomic system
   automatically reconfigures to minimise the operational impact.

4.3.  Eliminate management control and central policy

   Senior management might fear loss of control of an autonomic network.
   In fact this is no more likely than with a traditional network; the
   emphasis on automatically applying general policy and security rules
   might even provide more management control.

4.4.  Eliminate existing configuration tools

   While autonomic networks will rarely need manual intervention, there
   is no expectation that traditional top-down configuration tools will
   vanish immediately.  Autonomic techniques will have to co-exist with
   them, and they will survive for as long as they are useful.
   Initially they will certainly play a part in confidence-building in
   the autonomic method, and they will be held in reserve for emergency
   use for a long time.

4.5.  Eliminate existing network management systems

   Existing monitoring and reporting systems will continue to be needed,
   and as just noted existing configuration mechanisms will not vanish.
   Therefore, it is to be expected that the existing NMS will be



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   retained in parallel with autonomic mechanisms, and will be adapted
   as necessary.  Some aspects of the autonomic mechanism (e.g.
   aggregated reporting, exception reporting) should indeed be
   integrated with the existing NMS as far as possible.

5.  Guidelines for Case Studies

   [This section is work in progress.]

6.  An Autonomic Reference Model

   An Autonomic Network consists of Autonomic Nodes.  Those nodes
   communicate with each other through an Autonomic Control Plane which
   provides a robust and secure communications overlay.  The Autonomic
   Control Plane is self-organizing and autonomic itself.

   An Autonomic Node contains various elements, such as autonomic
   service agents.  Figure 1 shows a reference model of an autonomic
   node.  The elements and their interaction are:

   o  Autonomic Service Agents, which implement the autonomic behaviour
      of a specific service or function.

   o  Self-knowledge: An autonomic node knows its own properties and
      capabilities

   o  Network Knowledge (Discovery): An autonomic service agent may
      require various discovery functions in the network, such as
      service discovery.

   o  Intent: Network wide high level policy.  Autonomic Service Agents
      use an intent interpretation engine to locally instantiate the
      global intent.  This may involve coordination with other Autonomic
      Nodes.

   o  Feedback Loops: Control elements outside the node may interact
      with autonomic nodes through feedback loops.

   o  An Autonomic User Agent, providing a front-end to external users
      (administrators and management applications) through which they
      can communicate intent, receive reports, and monitor the Autonomic
      Network.

   o  Autonomic Control Plane: Allows the node to communicate with other
      autonomic nodes.  Autonomic functions such as intent distribution,
      feedback loops, discovery mechanisms, etc, use the autonomic
      control plane.




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   +------------------------------------------------------------+
   |               +----------+ +--------------+                |
   |               |          | | Feedback     |                |
   |               | Intent   | |    Loops     |                |
   |               +----------+ +--------------+                |
   |                         ^     ^                            |
   |                    Autonomic User Agent                    |
   |                         V     V                            |
   | +-----------+        +------------+        +------------+  |
   | | Self-     |        | Autonomic  |        | Network    |  |
   | | knowledge |<------>| Service    |<------>| Knowledge  |  |
   | |           |        | Agents     |        | (Discovery)|  |
   | +-----------+        +------------+        +------------+  |
   |                            ^                     ^         |
   |                            |                     |         |
   |                            V                     V         |
   |------------------------------------------------------------|
   |                 Autonomic Control Plane                    |
   |------------------------------------------------------------|
   |           Standard Operating System Functions              |
   +------------------------------------------------------------+

                                 Figure 1

7.  Security Considerations

   This document specifies a framework.  Security is an integral part of
   this framework.

8.  Acknowledgements

   The work on Autonomic Networking is the result of a large team
   project at Cisco Systems.  In alphabetical order: Ignas Bagdonas,
   Parag Bhide, Balaji BL, Toerless Eckert, Yves Hertoghs, Bruno
   Klauser.

   The ETSI working group AFI (http://portal.etsi.org/afi) defines a
   similar framework for autonomic networking in the "General Autonomic
   Network Architecture" [GANA].  Many concepts explained in this
   document can be mapped to the GANA framework.  The mapping is outside
   the scope of this document.  Special thanks to Ranganai Chaparadza
   for his comments and help on this document.

9.  Informative References







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   [GANA]     ETSI GS AFI 002, , "Autonomic network engineering for the
              self-managing Future Internet (AFI): GANA Architectural
              Reference Model for Autonomic Networking, Cognitive
              Networking and Self-Management.", April 2013,
              <http://www.etsi.org/deliver/etsi_gs/AFI/001_099/002/
              01.01.01_60/gs_afi002v010101p.pdf>.

   [Kephart]  Kephart, J. and D. Chess, "The Vision of Autonomic
              Computing", IEEE Computer vol. 36, no. 1, pp. 41-50,
              January 2003.

Authors' Addresses

   Michael Behringer
   Cisco Systems
   Building D, 45 Allee des Ormes
   Mougins  06250
   France

   Email: mbehring@cisco.com


   Max Pritikin
   Cisco Systems

   Email: pritikin@cisco.com


   Steinthor Bjarnason
   Cisco Systems

   Email: sbjarnas@cisco.com


   Alex Clemm
   Cisco Systems

   Email: alex@cisco.com


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

   Email: brian.e.carpenter@gmail.com



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   Sheng Jiang
   Huawei Technologies Co., Ltd
   Q14, Huawei Campus
   No.156 Beiqing Road
   Hai-Dian District, Beijing  100095
   P.R. China

   Email: jiangsheng@huawei.com


   Laurent Ciavaglia
   Alcatel-Lucent

   Email: Laurent.Ciavaglia@alcatel-lucent.com





































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