Abstract
In order to properly distribute sensor nodes in wireless sensor networks, a coverage model considering maximum coverage ratio and minimum redundancy is given and the optimization strategy based on quantum-inspired cultural algorithm is proposed. In population space, quantum-inspired evolutionary algorithm is used to increase the observed probability. In belief space, the implicit knowledge embodied in the evolution is extracted from the better individuals chosen from the population. It is used to guide the search direction of evolutionary population and influence the update of quantum individuals. Simulation results indicate that the algorithm is superior to other algorithms in coverage optimization and effectively improve the coverage performance of wireless sensor networks.
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Acknowledgments
This work was supported by Natural Science Foundation of Jiangsu under Grant BK2010183, the Fundamental Research Funds for the Central Universities under Grant 2012LWB76 and Jiangsu Overseas Research & Training Program for University Prominent Young & Middle-aged Teachers and Presidents.
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Guo, Yn., Liu, D., Liu, Y., Chen, M. (2013). The Coverage Optimization for Wireless Sensor Networks Based on Quantum-Inspired Cultural Algorithm. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38524-7_9
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DOI: https://doi.org/10.1007/978-3-642-38524-7_9
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