Abstract
Motivated by the need for agent classification in sensor networking and autonomous vehicle control applications, we propose 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 need for new algorithms for network partitioning and distributed (or self-) partitioning. We then review our stochastic automaton-based partitioning algorithm, and extend its use for network partitioning and self-partitioning problems. Finally, the application of the algorithm to mobile/sensor classification in ad hoc networks is pursued in detail, and other applications are briefly introduced.
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Correspondence should be sent to the first author at sroy@eecs.wsu.edu. The first and third authors were partially supported by the National Science Foundation under Grant ECS-0528882 (Sensors), and the third author was also partially supported by the Office of Naval Research under Grant N000140310848.
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© 2006 Springer-Verlag Berlin Heidelberg
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Roy, S., Wan, Y., Saberi, A. (2006). A Flexible Algorithm for Sensor Network Partitioning and Self-partitioning Problems. In: Nikoletseas, S.E., Rolim, J.D.P. (eds) Algorithmic Aspects of Wireless Sensor Networks. ALGOSENSORS 2006. Lecture Notes in Computer Science, vol 4240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11963271_14
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DOI: https://doi.org/10.1007/11963271_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69085-6
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