Genetic Programming for Lifetime Maximization in Wireless Sensor Networks with a Mobile Sink

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Li:2017:SEAL,

• author = "Ying Li and Zhixing Huang and Jinghui Zhong and Liang Feng",
• title = "Genetic Programming for Lifetime Maximization in Wireless Sensor Networks with a Mobile Sink",
• booktitle = "Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL-2017",
• year = "2017",
• editor = "Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin",
• volume = "10593",
• series = "Lecture Notes in Computer Science",
• pages = "774--785",
• address = "Shenzhen, China",
• month = nov # " 10-13",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-68759-9",
• URL = "https://doi.org/10.1007/978-3-319-68759-9_63",
• DOI = "doi:10.1007/978-3-319-68759-9_63",
• 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.",

}

Genetic Programming entries for Ying Li Zhixing Huang Jinghui Zhong Liang Feng

Citations