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

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

@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