Randomized smoothing networks

Authors:
Maurice Herlihy;Srikanta Tirthapura
Affiliations:
Computer Science Department, Brown University, Providence, RI, USA;Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA
Venue:
Journal of Parallel and Distributed Computing - Special issue: 18th International parallel and distributed processing symposium
Year:
2006

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Abstract

A smoothing network is a distributed data structure that accepts tokens on input wires and routes them to output wires. It ensures that however imbalanced the traffic on input wires, the numbers of tokens emitted on output wires are approximately balanced. We study randomized smoothing networks, whose initial states are chosen at random. Randomized smoothing networks require no global initialization, and also require no global reconfiguration after faults. We show that the randomized version of the well-known block smoothing network is 2.36log(w)-smooth with high probability, where w is the number of input or output wires. As a direct consequence, we prove that the randomized bitonic and periodic networks are also O(log(w))-smooth with high probability. In contrast, it is known that these networks are (logw)-smooth in the worst case.