Stateless distributed algorithms for near optimal maximum multicommodity flows

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Stateless distributed algorithms for near optimal maximum multicommodity flows

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Annual ACM Symposium on Principles of Distributed Computing archive
Proceedings of the twenty-seventh ACM symposium on Principles of distributed computing table of contents

Toronto, Canada

SESSION: B3-1 table of contents

Pages 440-440

Year of Publication: 2008

ISBN:978-1-59593-989-0

Authors

Baruch Awerbuch	Johns Hopkins University, Baltimore, MD, USA
Rohit Khandekar	IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

Sponsors

SIGOPS: ACM Special Interest Group on Operating Systems
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory

Publisher

ACM New York, NY, USA

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ABSTRACT

We design a stateless and distributed solution to the problem of maximum multicommodity flows--route the maximum amount of flow between given source-sink pairs, possibly split along several paths, subject to edge-capacity constraints. Our main contribution is in extending the work of [1,2] to the case where the flow can be routed along possibly exponentially many different paths. Our algorithm, starting from an arbitrary feasible flow, always maintains a feasible flow, and reaches a 1 + ε approximation of maximum benefit value in Õ(n²) rounds.

REFERENCES

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	1	B. Awerbuch and R. Khandekar. Stateless near optimal flow control with poly-logarithmic convergence. In LATIN, 2008.
	2	Baruch Awerbuch , Rohit Khandekar, Stateless distributed gradient descent for positive linear programs, Proceedings of the 40th annual ACM symposium on Theory of computing, May 17-20, 2008, Victoria, British Columbia, Canada [doi>10.1145/1374376.1374476]