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Coverage Optimization for Wireless Sensor Networks by Evolutionary Algorithm

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Computational Intelligence and Intelligent Systems (ISICA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

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Abstract

Wireless sensor network consists of a large number of tiny sensor nodes owned capable of perception in monitoring region by self-organized wireless communication, has been widely applied in military and civil fields. From the perspective of resource- saving, under the condition of the network’s connectivity and specific coverage, the number of sensor nodes is assumed to be opened as few as possible. So, computing the sensor nodes collection which meeting the requirements is called the problem of network coverage optimization for Wireless Sensor Network; also called the problem of minimum connected covering node set. The innovation point of the article is: Firstly, it analyzed the deficiencies of traditional evolution algorithm fitness function, put forward an improved fitness function design scheme, and has been proved that it has advantage of solving problem on wireless sensor networks coverage optimization; Secondly, it applied the method of control variables, comparison and analysis of the influence on the various operations and parameters selection in evolution algorithm on the optimization results and performance, and then point out how to design algorithm to manage to the best optimize effect and performance.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China with the Grant No. 61573157, the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454.

This work was jointly supported by Natural Science Foundation of Guangdong Province of China (#2015A030313408).

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Correspondence to Zhichao Wen .

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Li, K., Wen, Z., Li, S. (2016). Coverage Optimization for Wireless Sensor Networks by Evolutionary Algorithm. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_6

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  • DOI: https://doi.org/10.1007/978-981-10-0356-1_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

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