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A Flexible Stochastic Automaton-Based Algorithm for Network Self-Partitioning

Author

Listed:
  • Yan Wan
  • Sandip Roy
  • Ali Saberi
  • Bernard Lesieutre

Abstract

This article proposes a flexible and distributed stochastic automaton-based network partitioning algorithm that is capable of finding the optimal k-way partition with respect to a broad range of cost functions, and given various constraints, in directed and weighted graphs. Specifically, we motivate the distributed partitioning (self-partitioning) problem, introduce the stochastic automaton-based partitioning algorithm, and show that the algorithm finds the optimal partition with probability 1 for a large class of partitioning tasks. Also, a discussion of why the algorithm can be expected to find good partitions quickly is included, and its performance is further illustrated through examples. Finally, applications to mobile/sensor classification in ad hoc networks, fault-isolation in electric power systems, and control of autonomous vehicle teams are pursued in detail.

Suggested Citation

  • Yan Wan & Sandip Roy & Ali Saberi & Bernard Lesieutre, 2008. "A Flexible Stochastic Automaton-Based Algorithm for Network Self-Partitioning," International Journal of Distributed Sensor Networks, , vol. 4(3), pages 223-246, July.
    • Handle: RePEc:sae:intdis:v:4:y:2008:i:3:p:223-246
    DOI: 10.1080/15501320701260063
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