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Prolonging Lifetime in Wireless Sensor Networks with Interference Constraints

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Green, Pervasive, and Cloud Computing (GPC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10232))

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Abstract

In this work, we consider a scenario in which we have to monitor some locations of interest in a geographical area by means of a wireless sensor network. Our aim is to keep the network operational for as long as possible, while preventing certain sensors from being active simultaneously, since they would interfere with one another causing data loss, need for retransmissions and overall affecting the throughput and efficiency of the network. We propose an exact approach based on column generation, as well as a heuristic algorithm to solve its separation problem. Computational tests prove our approach to be effective, and that the introduction of our heuristic in the Column Generation framework allows significant gains in terms of required computational effort.

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Authors and Affiliations

  1. Department of Mathematics, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, Salerno, Italy

    Francesco Carrabs, Raffaele Cerulli, Ciriaco D’Ambrosio & Andrea Raiconi

Authors
  1. Francesco Carrabs
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  2. Raffaele Cerulli
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  3. Ciriaco D’Ambrosio
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  4. Andrea Raiconi
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Corresponding author

Correspondence to Ciriaco D’Ambrosio .

Editor information

Editors and Affiliations

  1. Hong Kong Polytechnic University, Hong Kong, Hong Kong

    Man Ho Allen Au

  2. University of Salerno, Fisciano, Italy

    Arcangelo Castiglione

  3. University of Texas at San Antonio, San Antonio, Texas, USA

    Kim-Kwang Raymond Choo

  4. University of Salerno, Fisciano, Italy

    Francesco Palmieri

  5. Providence University, Taichung City, Taiwan

    Kuan-Ching Li

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Carrabs, F., Cerulli, R., D’Ambrosio, C., Raiconi, A. (2017). Prolonging Lifetime in Wireless Sensor Networks with Interference Constraints. In: Au, M., Castiglione, A., Choo, KK., Palmieri, F., Li, KC. (eds) Green, Pervasive, and Cloud Computing. GPC 2017. Lecture Notes in Computer Science(), vol 10232. Springer, Cham. https://doi.org/10.1007/978-3-319-57186-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-57186-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57185-0

  • Online ISBN: 978-3-319-57186-7

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