Abstract
Maximizing the lifetime of Wireless Sensor Network (WSN) with a mobile sink is a challenging and important problem that has attracted increasing research attentions. In the literature, heuristic based approaches have been proposed to solve the problem, such as the Greedy Maximum Residual Energy (GMRE) based method. However, existing heuristic based approaches highly rely on expert knowledge, which makes them inconvenient for practical applications. Taking this cue, in this paper, we propose an automatic method to construct heuristic for sink routing based on Genetic Programming (GP) approach. Empirical study shows that the proposed method can generate promising heuristics that achieve superior performance against existing methods with respect to the global lifetime of WSN.
The first author and the second author contributed equally to this work.
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Acknowledgment
This work is partially supported under the National Natural Science Foundation of China (Grant Nos. 61602181, 61603064), Fundamental Research Funds for the Central Universities (Grant No. 2017ZD053), Frontier Interdisciplinary Research Fund for the Central Universities (Grant No. 106112017CDJQJ188828).
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Li, Y., Huang, Z., Zhong, J., Feng, L. (2017). Genetic Programming for Lifetime Maximization in Wireless Sensor Networks with a Mobile Sink. In: Shi, Y., et al. Simulated Evolution and Learning. SEAL 2017. Lecture Notes in Computer Science(), vol 10593. Springer, Cham. https://doi.org/10.1007/978-3-319-68759-9_63
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DOI: https://doi.org/10.1007/978-3-319-68759-9_63
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