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A Learning Automata-Based Approach to Lifetime Optimization in Wireless Sensor Networks

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Artificial Intelligence and Soft Computing (ICAISC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12854))

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Abstract

The paper examines the problem of lifetime optimization in Wireless Sensor Networks with an application of a distributed \(\epsilon \)-Learning Automaton. The scheme aims to find a global activity schedule maximizing the network’s lifetime while monitoring some target areas with a given measure of requested coverage ratio. The proposed algorithm possesses all the advantages of a localized algorithm, i.e., using only limited knowledge about neighbors, the ability to self-organize in such a way as to prolong the lifetime, and, at the same time, preserving the required coverage ratio of the target field. We present the preliminary results of an experimental study comparing the proposed solution with two centralized algorithms providing an exact (Integer Linear Programming (ILP)) and approximated solution (Genetic Algorithm (GA)) of the studied problem.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Natural Sciences, Cardinal Stefan Wyszyński University, Warsaw, Poland

    Jakub Gąsior & Franciszek Seredyński

Authors
  1. Jakub Gąsior
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  2. Franciszek Seredyński
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Corresponding author

Correspondence to Jakub Gąsior .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Gąsior, J., Seredyński, F. (2021). A Learning Automata-Based Approach to Lifetime Optimization in Wireless Sensor Networks. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12854. Springer, Cham. https://doi.org/10.1007/978-3-030-87986-0_33

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  • DOI: https://doi.org/10.1007/978-3-030-87986-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87985-3

  • Online ISBN: 978-3-030-87986-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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