A wireless sensor network topology design method based on negotiable evolutionary algorithm

Hao Wen Lin, Li Zhang, Xinchang Hao, Tomohiro Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In Wireless Sensor Networks (WSN), the sensor nodes and its central node are located some distance apart to ensure good coverage over the concerning area. However, the communication distance between sensor nodes is directly proportional to power consumption, and the ultimate effective point-to-point distance is nevertheless limited. To overcome this problem, a cluster based layout formation and an message routing algorithm among the head node of each cluster are suggested to ensure a WSN achieve good coverage, balance workload and traffic-load, and prolong the overall network lifetime. In this paper, we use a Negotiable Evolutionary Algorithm (NEA) to solve the complex multi-object WSN layout and signal routing problem. Experiment result shows that NEA is an effective approach for solving the problem.

Original languageEnglish
Title of host publicationProceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012
Pages207-210
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012 - Kitakyushu, Japan
Duration: 2012 Aug 252012 Aug 28

Publication series

NameProceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012

Conference

Conference2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012
CountryJapan
CityKitakyushu
Period12/8/2512/8/28

Keywords

  • Evolutionary algorithm
  • Multi-objective optimization
  • Wireless sensor network

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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  • Cite this

    Lin, H. W., Zhang, L., Hao, X., & Murata, T. (2012). A wireless sensor network topology design method based on negotiable evolutionary algorithm. In Proceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012 (pp. 207-210). [6457138] (Proceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012). https://doi.org/10.1109/ICGEC.2012.37