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Cellular Automata Approach to Maximum Lifetime Coverage Problem in Wireless Sensor Networks

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Cellular Automata (ACRI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8751))

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Abstract

In this paper, we propose a novel distributed algorithm based on Graph Cellular Automata (GCA) concept to solve Maximum Lifetime Coverage Problem (MLCP) in Wireless Sensor Networks (WSNs). The proposed algorithm possesses all advantages of localized algorithm, i.e. using only some knowledge about the neighbors, WSN is able to self-organize in such a way to prolong its lifetime preserving at the same time required coverage ratio of a target field. The paper presents results of experimental study of the proposed algorithm and comparison of them with a centralized genetic algorithm.

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Author information

Authors and Affiliations

  1. Dep. of Mathematics and Natural Sciences, Cardinal Stefan Wyszynski University in Warsaw, Woycickiego 1/3, 01-938, Warsaw, Poland

    Antonina Tretyakova & Franciszek Seredynski

  2. CSC Research Unit, University of Luxembourg, 6, rue Richard Coudenhoven-Kalergi, L-1359, Luxembourg

    Pascal Bouvry

Authors
  1. Antonina Tretyakova
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  2. Franciszek Seredynski
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  3. Pascal Bouvry
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Editor information

Editors and Affiliations

  1. Dept. of Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059, Krakow, Poland

    Jarosław Wąs

  2. Dept. of Electrical and Computer Engineering, Democritus University of Thrace, 67100, Xanthi, Greece

    Georgios Ch. Sirakoulis

  3. CSAI - Complex Systems and Artificial Intelligence Research Center, University of Milano-Bicocca, 20126, Milan, Italy

    Stefania Bandini

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© 2014 Springer International Publishing Switzerland

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Tretyakova, A., Seredynski, F., Bouvry, P. (2014). Cellular Automata Approach to Maximum Lifetime Coverage Problem in Wireless Sensor Networks. In: Wąs, J., Sirakoulis, G.C., Bandini, S. (eds) Cellular Automata. ACRI 2014. Lecture Notes in Computer Science, vol 8751. Springer, Cham. https://doi.org/10.1007/978-3-319-11520-7_45

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  • DOI: https://doi.org/10.1007/978-3-319-11520-7_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11519-1

  • Online ISBN: 978-3-319-11520-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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