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InterCriteria Analysis of Different Variants of ACO Algorithm for Wireless Sensor Network Positioning

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Numerical Methods and Applications (NMA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11189))

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Abstract

Wireless sensor networks are formed by spatially distributed sensors, which communicate in a wireless way. This network can monitor various kinds of environment and physical conditions like movement, noise, light, humidity, images, chemical substances etc. A given area needs to be fully covered with minimal number of sensors and the energy consumption of the network needs to be minimal too. We propose several algorithms, based on Ant Colony Optimization, to solve the problem. We study the algorithms behaviour when the number of ants varies from 1 to 10. We apply InterCriteria analysis to study relations between proposed algorithms and number of ants and analyse correlation between them.

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Acknowledgments

Work presented here is partially supported by the Bulgarian National Scientific Fund under Grants DFNI DN 12/5 “Efficient Stochastic Methods and Algorithms for Large-Scale Problems” and DN 02/10“New Instruments for Knowledge Discovery from Data, and their Modelling”.

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Authors and Affiliations

  1. Institute of Information and Communication Technologies – BAS, Acad. G. Bonchev Str., bl. 25A, 1113, Sofia, Bulgaria

    Stefka Fidanova

  2. Institute of Biophysics and Biomedical Engineering – BAS, Acad. G. Bonchev Str., bl. 105, 1113, Sofia, Bulgaria

    Olympia Roeva

Authors
  1. Stefka Fidanova
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  2. Olympia Roeva
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Correspondence to Stefka Fidanova .

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Editors and Affiliations

  1. Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria

    Geno Nikolov

  2. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Natalia Kolkovska

  3. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir Georgiev

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Fidanova, S., Roeva, O. (2019). InterCriteria Analysis of Different Variants of ACO Algorithm for Wireless Sensor Network Positioning. In: Nikolov, G., Kolkovska, N., Georgiev, K. (eds) Numerical Methods and Applications. NMA 2018. Lecture Notes in Computer Science(), vol 11189. Springer, Cham. https://doi.org/10.1007/978-3-030-10692-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-10692-8_10

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  • Print ISBN: 978-3-030-10691-1

  • Online ISBN: 978-3-030-10692-8

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