Dynamic-Anycast in Compute First Networking (CFN-Dyncast) Use Cases and Problem Statement
draft-geng-rtgwg-cfn-dyncast-ps-usecase-00

Document Type Active Internet-Draft (individual)
Authors Liang Geng  , Peng Liu  , Peter Willis 
Last updated 2020-10-30
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rtgwg                                                            L. Geng
Internet-Draft                                                    P. Liu
Intended status: Informational                              China Mobile
Expires: May 3, 2021                                           P. Willis
                                                                      BT
                                                        October 30, 2020

Dynamic-Anycast in Compute First Networking (CFN-Dyncast) Use Cases and
                           Problem Statement
               draft-geng-rtgwg-cfn-dyncast-ps-usecase-00

Abstract

   Service providers are exploring the edge computing to achieve better
   response time, control over data and carbon energy saving by moving
   the computing services towards the edge of the network in scenarios
   of 5G MEC (Multi-access Edge Computing), virtualized central office,
   and others.  Providing services by sharing computing resources from
   multiple edges is emerging and becoming more and more useful for
   computationally intensive tasks.  The service nodes attached to
   multiple edges normally have two key features, service equivalency
   and service dynamism.  Ideally they should serve the service in a
   computational balanced way.  However lots of approaches dispatch the
   service in a static way, e.g., to the geographically closest edge,
   and they may cause unbalanced usage of computing resources at edges
   which further degrades user experience and system utilization.  This
   draft provides an overview of scenarios and problems associated.

   Networking taking account of computing resource metrics as one of its
   top parameters is called Compute First Networking (CFN) in this
   document.  The document identifies several key areas which require
   more investigations in architecture and protocol to achieve the
   balanced computing and networking resource utilization among edges in
   CFN.

Status of This Memo

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Geng, et al.               Expires May 3, 2021                  [Page 1]
Internet-Draft     CFN-Dyncast Use Cases and Problems       October 2020

   time.  It is inappropriate to use Internet-Drafts as reference
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   This Internet-Draft will expire on May 3, 2021.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Definition of Terms . . . . . . . . . . . . . . . . . . . . .   4
   3.  Main Use-Cases  . . . . . . . . . . . . . . . . . . . . . . .   4
     3.1.  Cloud Based Recognition in Augmented Reality (AR) . . . .   4
     3.2.  Connected Car . . . . . . . . . . . . . . . . . . . . . .   5
     3.3.  Cloud Virtual Reality (VR)  . . . . . . . . . . . . . . .   5
   4.  Requirements  . . . . . . . . . . . . . . . . . . . . . . . .   6
   5.  Problems Statement  . . . . . . . . . . . . . . . . . . . . .   6
     5.1.  Anycast based service addressing methodology  . . . . . .   7
     5.2.  Flow affinity . . . . . . . . . . . . . . . . . . . . . .   7
     5.3.  Computing Aware Routing . . . . . . . . . . . . . . . . .   8
   6.  Summary . . . . . . . . . . . . . . . . . . . . . . . . . . .   8
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .   9
   8.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   9
   9.  Informative References  . . . . . . . . . . . . . . . . . . .   9
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   Edge computing aims to provide better response times and transfer
   rate, with respect to Cloud Computing, by moving the computing
   towards the edge of the network.  Edge computing can be built on
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