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Multi-objective ACO Algorithm for WSN Layout: InterCriteria Analisys

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Large-Scale Scientific Computing (LSSC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11958))

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Abstract

One of the key objectives during wireless sensor networks deployment is full coverage of the monitoring region with a minimal number of sensors and minimized energy consumption of the network. In this paper we apply multi-objective Ant Colony Optimization (ACO) to solve this hard, from the computational point of view telecommunication problem. The number of ants is one of the key algorithm parameters in the ACO and it is important to find the optimal number of ants needed to achieve good solutions with minimal computational resources. The InterCriteria Analisys is applied in order to study the influence of ants number on the algorithm performance.

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Acknowledgment

This work is partially supported by the Projects: KP-06-N22/1 “Theoretical Research and Applications of InterCriteria Analysis” and by the Bulgarian Scientific Fund by the granr DN 12/5.

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Authors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Stefka Fidanova

  2. Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Olympia Roeva

Authors
  1. Stefka Fidanova
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  2. Olympia Roeva
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Corresponding author

Correspondence to Stefka Fidanova .

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Editors and Affiliations

  1. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Ivan Lirkov

  2. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Svetozar Margenov

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Fidanova, S., Roeva, O. (2020). Multi-objective ACO Algorithm for WSN Layout: InterCriteria Analisys. In: Lirkov, I., Margenov, S. (eds) Large-Scale Scientific Computing. LSSC 2019. Lecture Notes in Computer Science(), vol 11958. Springer, Cham. https://doi.org/10.1007/978-3-030-41032-2_57

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  • DOI: https://doi.org/10.1007/978-3-030-41032-2_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41031-5

  • Online ISBN: 978-3-030-41032-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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