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Energy Efficient Clustering for Wireless Sensor Networks: A Gravitational Search Algorithm

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9873))

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Abstract

Clustering is an efficient technique for saving energy of wireless sensor networks (WSNs). In this paper, a Gravitational Search Algorithm (GSA) based approach has been presented called GSA-EEC (GSA based Energy Efficient Clustering). The algorithm is designed with an efficient encoding scheme of an and a new fitness function. For the efficient design of WSNs. we consider the Euclidian distance from the sensors to gateways and gateways to sink and residual energy of gateways. The GSA-EEC is simulated extensively with varying number of sensor and gateways and various scenarios of WSNs. To show the efficacy of the GSA-EEC, we compared with some of the benchmark clustering algorithms.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, 826004, India

    P. C. Srinivasa Rao, Haider Banka & Prasanta K. Jana

Authors
  1. P. C. Srinivasa Rao
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  2. Haider Banka
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  3. Prasanta K. Jana
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Corresponding author

Correspondence to P. C. Srinivasa Rao .

Editor information

Editors and Affiliations

  1. IIT, New Dehli, India

    Bijaya Ketan Panigrahi

  2. Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  4. Department of Computer Science Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

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© 2016 Springer International Publishing AG

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Srinivasa Rao, P.C., Banka, H., Jana, P.K. (2016). Energy Efficient Clustering for Wireless Sensor Networks: A Gravitational Search Algorithm. In: Panigrahi, B., Suganthan, P., Das, S., Satapathy, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2015. Lecture Notes in Computer Science(), vol 9873. Springer, Cham. https://doi.org/10.1007/978-3-319-48959-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-48959-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48958-2

  • Online ISBN: 978-3-319-48959-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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