PSO based wireless sensor networks coverage optimization on DEMs
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
International Journal of Sensor Networks
A swarm intelligence based distributed localization technique for wireless sensor network
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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Proceedings of the 7th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks
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Applied Computational Intelligence and Soft Computing
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Wireless-sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environment. Developers of WSNs face challenges that arise from communication link failures, memory and computational constraints, and limited energy. Many issues in WSNs are formulated as multidimensional optimization problems, and approached through bioinspired techniques. Particle swarm optimization (PSO) is a simple, effective, and computationally efficient optimization algorithm. It has been applied to address WSN issues such as optimal deployment, node localization, clustering, and data aggregation. This paper outlines issues in WSNs, introduces PSO, and discusses its suitability for WSN applications. It also presents a brief survey of how PSO is tailored to address these issues.