Weighted HRW and its applications
draft-ietf-bess-weighted-hrw-00
Document | Type |
This is an older version of an Internet-Draft whose latest revision state is "Active".
Expired & archived
|
|
---|---|---|---|
Authors | SATYA R MOHANTY , Mankamana Prasad Mishra , Acee Lindem , Ali Sajassi , John Drake | ||
Last updated | 2023-09-01 (Latest revision 2023-02-28) | ||
Replaces | draft-mohanty-bess-weighted-hrw | ||
RFC stream | Internet Engineering Task Force (IETF) | ||
Formats | |||
Additional resources | Mailing list discussion | ||
Stream | WG state | WG Document | |
Document shepherd | (None) | ||
IESG | IESG state | Expired | |
Consensus boilerplate | Unknown | ||
Telechat date | (None) | ||
Responsible AD | (None) | ||
Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
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.
Authors
SATYA R MOHANTY
Mankamana Prasad Mishra
Acee Lindem
Ali Sajassi
John Drake
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)