Distributed SFC control for fog environments
draft-bernardos-sfc-distributed-control-00

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SFC WG                                                     CJ. Bernardos
Internet-Draft                                                      UC3M
Intended status: Experimental                                  A. Mourad
Expires: January 9, 2020                                    InterDigital
                                                            July 8, 2019

              Distributed SFC control for fog environments
               draft-bernardos-sfc-distributed-control-00

Abstract

   Service function chaining (SFC) allows the instantiation of an
   ordered set of service functions and subsequent "steering" of traffic
   through them.  In order to set up and maintain SFC instances, a
   control plane is required, which typically is centralized.  In
   certain environments, such as fog computing ones, such centralized
   control might not be feasible, calling for distributed SFC control
   solutions.  This document introduces the role of SFC pseudo-
   controller and specifies solutions to select and initialize such new
   logical function.

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   This Internet-Draft will expire on January 9, 2020.

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   This document is subject to BCP 78 and the IETF Trust's Legal
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Bernardos & Mourad       Expires January 9, 2020                [Page 1]
Internet-Draft           Distributed SFC control               July 2019

   carefully, as they describe your rights and restrictions with respect
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   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Problem statement . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Distributed SFC control . . . . . . . . . . . . . . . . . . .   6
     4.1.  SFC pseudo controller initialization  . . . . . . . . . .   7
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  11
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .  11
   7.  Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .  11
   8.  Informative References  . . . . . . . . . . . . . . . . . . .  12
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  12

1.  Introduction

   Virtualization of functions provides operators with tools to deploy
   new services much faster, as compared to the traditional use of
   monolithic and tightly integrated dedicated machinery.  As a natural
   next step, mobile network operators need to re-think how to evolve
   their existing network infrastructures and how to deploy new ones to
   address the challenges posed by the increasing customers' demands, as
   well as by the huge competition among operators.  All these changes
   are triggering the need for a modification in the way operators and
   infrastructure providers operate their networks, as they need to
   significantly reduce the costs incurred in deploying a new service
   and operating it.  Some of the mechanisms that are being considered
   and already adopted by operators include: sharing of network
   infrastructure to reduce costs, virtualization of core servers
   running in data centers as a way of supporting their load-aware
   elastic dimensioning, and dynamic energy policies to reduce the
   monthly electricity bill.  However, this has proved to be tough to
   put in practice, and not enough.  Indeed, it is not easy to deploy
   new mechanisms in a running operational network due to the high
   dependency on proprietary (and sometime obscure) protocols and
   interfaces, which are complex to manage and often require configuring
   multiple devices in a decentralized way.

   Service Functions are widely deployed and essential in many networks.
   These Service Functions provide a range of features such as security,
   WAN acceleration, and server load balancing.  Service Functions may
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