Weighted HRW and its applications
draft-mohanty-bess-weighted-hrw-00

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BESS Working Group                                            S. Mohanty
Internet-Draft                                                  M. Misra
Intended status: Standards Track                               A. Lindem
Expires: September 12, 2019                                   A. Sajassi
                                                     Cisco Systems, Inc.
                                                          March 11, 2019

                   Weighted HRW and its applications
                   draft-mohanty-bess-weighted-hrw-00

Abstract

   Rendezvous Hashing also known as Highest Random Weight (HRW) has been
   used in many load balancing applications where the central problem is
   how to map an object to as server such that the mapping is uniform
   and also minimally affected by the change in the server set.
   Recently, it has found use in DF election algorithms in the EVPN
   context and load balancing using DMZ.  This draft deals with the
   problem of achieving load balancing with minimal disruption when the
   servers have different weights.  It provides an algorithm to do so
   and also describes a few use-case scenarios where this algorithmic
   technique can apply.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
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   This Internet-Draft will expire on September 12, 2019.

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   Copyright (c) 2019 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

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Table of Contents

   1.  Requirements Language . . . . . . . . . . . . . . . . . . . .   2
   2.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   3.  HRW Introduction  . . . . . . . . . . . . . . . . . . . . . .   3
   4.  HRW with weights  . . . . . . . . . . . . . . . . . . . . . .   4
   5.  HRW and Consistent Hashing  . . . . . . . . . . . . . . . . .   5
   6.  Weighted HRW and its application to the EVPN DF Election  . .   5
   7.  Weighted HRW and its application to Resilient Hashing . . . .   7
   8.  Weighted HRW and its application to Multicast DR Election . .   7
   9.  Protocol Considerations . . . . . . . . . . . . . . . . . . .   8
   10. Operational Considerations  . . . . . . . . . . . . . . . . .   8
   11. Security Considerations . . . . . . . . . . . . . . . . . . .   8
   12. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .   8
   13. References  . . . . . . . . . . . . . . . . . . . . . . . . .   8
     13.1.  Normative References . . . . . . . . . . . . . . . . . .   8
     13.2.  Informative References . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  10

1.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in [RFC2119].

2.  Introduction

   Given an object O, a set of servers and a set of clients, a
   fundamental problem is how do the set of clients, independently and
   unanimously agree in a distributed framework, which server to assign
   O?  This is the distributed hash table problem.  The assignment
   should be "minimally disruptive" which means that there should be a
   minimal remapping of objects whenever a server is down or a new
   server comes up or the object set changes.  This is a very common
   problem in practice in the Internet load balancing and web caching as
   described in the 'Akamai' paper [CHASH], database [DYNAMODB] and
   networking context.

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