Summary: Distributed Algorithms for Multicommodity Flow Problems via Approximate
Steepest Descent Framework
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
Previously known solutions that achieved comparable
convergence time and approximation ratio required exponen-
tial computational and space overhead per agent.