Weighted HRW and its applications
draft-mohanty-bess-weighted-hrw-02
| Document | Type |
Replaced Internet-Draft
(individual)
Expired & archived
|
|
|---|---|---|---|
| Authors | satyamoh@cisco.com , Mankamana Prasad Mishra , Acee Lindem , Ali Sajassi , John Drake | ||
| Last updated | 2021-06-11 (Latest revision 2020-12-08) | ||
| Replaced by | draft-ietf-bess-weighted-hrw | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Replaced by draft-ietf-bess-weighted-hrw | |
| 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This Internet-Draft is no longer active.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
satyamoh@cisco.com
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.)