Message passing for task redistribution on sparse graphs

Part of Advances in Neural Information Processing Systems 18 (NIPS 2005)

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K. Y. Michael Wong, David Saad, Zhuo Gao


The problem of resource allocation in sparse graphs with real variables is studied using methods of statistical physics. An ef´Čücient distributed algorithm is devised on the basis of insight gained from the analysis and is examined using numerical simulations, showing excellent performance and full agreement with the theoretical results.