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Distributed selfish load balancing.

Berenbrink, P. and Friedetzky, T. and Goldberg, L. A. and Goldberg, P. and Hu, Z. and Martin, R. (2006) 'Distributed selfish load balancing.', in Proceedings of the 17th Annual ACM-SIAM Symposium on Discrete Algorithm. New York: Association for Computing Machinery, pp. 354-363.

Abstract

Suppose that a set of m tasks are to be shared as equally as possible amongst a set of n resources. A game-theoretic mechanism to find a suitable allocation is to associate each task with a "selfish agent", and require each agent to select a resource, with the cost of a resource being the number of agents to select it. Agents would then be expected to migrate from overloaded to underloaded resources, until the allocation becomes balanced.Recent work has studied the question of how this can take place within a distributed setting in which agents migrate selfishly without any centralized control. In this paper we discuss a natural protocol for the agents which combines the following desirable features: It can be implemented in a strongly distributed setting, uses no central control, and has good convergence properties. For m ≫ n, the system becomes approximately balanced (an ε-Nash equilibrium) in expected time O(log log m). We show using a martingale technique that the process converges to a perfectly balanced allocation in expected time O(log log m + n4). We also give a lower bound of Ω (max{log log m, n}) for the convergence time.

Item Type:Book chapter
Additional Information:Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms held Miami, FL, January 22–24, 2006.
Full text:Full text not available from this repository.
Publisher Web site:http://dx.doi.org/10.1145/1109557.1109597
Record Created:23 Jan 2009
Last Modified:08 Nov 2010 12:32

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