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Estimation Localization in Wireless Sensor Network Based on Multi-objective Grey Wolf Optimizer

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Advances in Information and Communication Technology (ICTA 2016)

Abstract

Determining the position of nodes of a network plays an important role in many wireless sensor networks (WSN) applications e.g. in tracking, detecting, monitoring, etc. In this paper, the multi-objective grey wolf optimizer (MGWO) for the estimating approaches of the located nodes in a network is proposed to solve the multi-objective optimization localization issues in WSNs. There two objective functions related to the estimation localization are the distance of nodes and the geometric topology that consider to formula multiobjective optimization localization. The simulation results show considerable improvements in terms of localization accuracy and convergence rate in comparison with those obtained from the other methods.

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Correspondence to Thi-Kien Dao .

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Nguyen, TT., Thom, H.T.H., Dao, TK. (2017). Estimation Localization in Wireless Sensor Network Based on Multi-objective Grey Wolf Optimizer. In: Akagi, M., Nguyen, TT., Vu, DT., Phung, TN., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2016. Advances in Intelligent Systems and Computing, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-319-49073-1_25

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  • DOI: https://doi.org/10.1007/978-3-319-49073-1_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49072-4

  • Online ISBN: 978-3-319-49073-1

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