Upward max min fairness

Emilie Danna, Avinatan Hassidim, Haim Kaplan, Alok Kumar, Yishay Mansour, Danny Raz, Michal Segalov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

30 Scopus citations

Abstract

Often one would like to allocate shared resources in a fair way. A common and well studied notion of fairness is Max-Min Fairness, where we first maximize the smallest allocation, and subject to that the second smallest, and so on. We consider a networking application where multiple commodities compete over the capacity of a network. In our setting each commodity has multiple possible paths to route its demand (for example, a network using MPLS tunneling). In this setting, the only known way of finding a max-min fair allocation requires an iterative solution of multiple linear programs. Such an approach, although polynomial time, scales badly with the size of the network, the number of demands, and the number of paths. More importantly, a network operator has limited control and understanding of the inner working of the algorithm. Finally, this approach is inherently centralized and cannot be implemented via a distributed protocol.

Original languageEnglish
Title of host publication2012 Proceedings IEEE INFOCOM, INFOCOM 2012
Pages837-845
Number of pages9
DOIs
StatePublished - 2012
Externally publishedYes
EventIEEE Conference on Computer Communications, INFOCOM 2012 - Orlando, FL, United States
Duration: 25 Mar 201230 Mar 2012

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Conference

ConferenceIEEE Conference on Computer Communications, INFOCOM 2012
Country/TerritoryUnited States
CityOrlando, FL
Period25/03/1230/03/12

Bibliographical note

Place of conference:USA

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