TY - GEN

T1 - Upward max min fairness

AU - Danna, Emilie

AU - Hassidim, Avinatan

AU - Kaplan, Haim

AU - Kumar, Alok

AU - Mansour, Yishay

AU - Raz, Danny

AU - Segalov, Michal

N1 - Place of conference:USA

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84861595536&partnerID=8YFLogxK

U2 - 10.1109/infcom.2012.6195832

DO - 10.1109/infcom.2012.6195832

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AN - SCOPUS:84861595536

SN - 9781467307758

T3 - Proceedings - IEEE INFOCOM

SP - 837

EP - 845

BT - 2012 Proceedings IEEE INFOCOM, INFOCOM 2012

T2 - IEEE Conference on Computer Communications, INFOCOM 2012

Y2 - 25 March 2012 through 30 March 2012

ER -