Abstract
Sensor deployment is an important issue in designing sensor networks. In this paper, particle swarm optimization (PSO) approach is applied to maximize the coverage based on a probabilistic sensor model in mobile sensor networks and to reduce cost by finding the optimal positions for the cluster-head nodes based on a well-known energy model. During the coverage optimization process, sensors move to form a uniformly distributed topology according to the execution of algorithm at base station. The simulation results show that PSO algorithm has faster convergence rate than genetic algorithm based method while achieving the goal of energy efficient sensor deployment.
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Wu, X., Lei, S., Jin, W., Cho, J., Lee, S. (2006). Energy-Efficient Deployment of Mobile Sensor Networks by PSO. In: Shen, H.T., Li, J., Li, M., Ni, J., Wang, W. (eds) Advanced Web and Network Technologies, and Applications. APWeb 2006. Lecture Notes in Computer Science, vol 3842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610496_50
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DOI: https://doi.org/10.1007/11610496_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31158-4
Online ISBN: 978-3-540-32435-5
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