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International Conference on Recent Trends in Image Processing and Pattern Recognition

RTIP2R 2018: Recent Trends in Image Processing and Pattern Recognition pp 735–745Cite as

A Review on Utilizing Bio-Mimetics in Solving Localization Problem in Wireless Sensor Networks

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1037))

Abstract

Wireless Sensor Networks (WSNs) have the feasibility to connect the physical world with the virtual world by framing a network of sensors. The supreme function of a sensor network is to collect and forward data to the destination. Applications based on WSNs needs location knowledge about randomly deployed nodes. Localization of these nodes is the basic problem in WSNs. Several types of research have been done so far, using various strategies to improve the network performance as well as energy efficiency and communications effectiveness of WSNs. Among the strategies used, algorithms inspired by natural behaviours of a group of organisms like butterflies, fireflies, grey wolf, etc., showed higher efficiency in locating the nodes. In this survey, some of the inherent nature inspired localization algorithms are briefly discussed. Also, some other collective behaviours which can be used to develop localization algorithms are also explained.

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Authors and Affiliations

  1. Vignan’s Foundation for Science, Technology and Research, Guntur, 522 213, Andhra Pradesh, India

    R. I. Malar & M. Shanmugam

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  1. R. I. Malar
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  2. M. Shanmugam
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Correspondence to M. Shanmugam .

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Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Malar, R.I., Shanmugam, M. (2019). A Review on Utilizing Bio-Mimetics in Solving Localization Problem in Wireless Sensor Networks. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_66

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  • DOI: https://doi.org/10.1007/978-981-13-9187-3_66

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