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Particle swarm optimization for the minimum energy broadcast problem in wireless ad-hoc networks

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3 Author(s)
Ping-Che Hsiao ; Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Tsung-Che Chiang ; Li-Chen Fu

In this paper, we propose a novel approach based on particle swarm optimization (PSO) for solving the minimum energy broadcast (MEB) problem, which has been proven to be NP-complete. Wireless sensor networks (WSNs) have attracted large intention in recent years due to its powerful ability. One crucial issue in WSN is energy saving because of the limited battery resource. The MEB problem is one of the important scenarios in WSN, where a node needs to broadcast packets to all other nodes in the network. The objective is to minimize power consumption of all nodes in the network. Here we take advantage of fast and guided convergence characteristics of PSO to solve the MEB problem. For applying PSO to the MEB problem, we use the power degree to define the particle position. We go a step further to analyze one well-known local search mechanism: r-shrink and propose an improved version. The experimental results show that the proposed approach is able to compete and even outperform state-of-the-art works.

Published in:

Evolutionary Computation (CEC), 2012 IEEE Congress on

Date of Conference:

10-15 June 2012