A cluster-merge algorithm for solving the minimum power broadcast problem in large scale wireless networks

Authors:
Arindam K. Das;Robert J. Marks;Mohamed El-Sharkawi;Payman Arabshahi;Andrew Gray
Affiliations:
Department of Electrical Engineering, University of Washington, Seattle, WA;Department of Electrical Engineering, University of Washington, Seattle, WA;Department of Electrical Engineering, University of Washington, Seattle, WA;Jet Propulsion Laboratory, Pasadena, CA;Jet Propulsion Laboratory, Pasadena, CA
Venue:
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
Year:
2003

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Abstract

In this paper, we address the minimum power broadcast problem in wireless networks. Assuming nodes are equipped with omni-directional antennas, the inherently broadcast nature of wireless networks can be exploited to compute power efficient routing trees. We propose a 2-stage cluster-merge algorithm for computing minimum power broadcast trees. The cluster phase is a look-ahead variant of the Broadcast Incremental Power algorithm [1] and the merge phase is a probabilistic positive reinforcement search procedure, as used in swarm intelligence algorithms. A local tree-improvement procedure is incorporated as an optional step in the merge phase to boost the performance of the algorithm. A key advantage of such a cluster based approach is significant reduction in time complexity. Simulations show that the algorithm is able to generate high quality solutions in relatively little computational time.