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Distributed Algorithms for Multicommodity Flow Problems via Approximate Steepest Descent Framework
 

Summary: Distributed Algorithms for Multicommodity Flow Problems via Approximate
Steepest Descent Framework
Baruch Awerbuch
Rohit Khandekar
Satish Rao
Abstract
We consider solutions for distributed multicommodity flow
problems, which are solved by multiple agents operating
in a cooperative but uncoordinated manner. We show
first distributed solutions that allow 1 + approximation
and whose convergence time is essentially linear in the
maximal path length, and is independent of the number of
commodities and the size of the graph.
Our algorithms use a very natural approximate steepest
descent framework, combined with a blocking flow technique
to speed up the convergence in distributed and parallel
environment.
Previously known solutions that achieved comparable
convergence time and approximation ratio required exponen-
tial computational and space overhead per agent.

  

Source: Awerbuch, Baruch - Department of Computer Science, Johns Hopkins University

 

Collections: Computer Technologies and Information Sciences