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Performance Analysis and Assessment of Various Energy Efficient Clustering-Based Protocols in WSN

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Computer Networks, Big Data and IoT

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 117))

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Abstract

Currently, the world is witnessing a rapid development in the area of wireless sensor networks. It holds a potential to transform many features of our economy and life, starting from bio diversity mapping to industry automation, transportation, healthcare monitoring. These networks primarily aim to develop protocols to utilize the sensor node energy efficiently and thereby maximize the lifetime of the network. In this research paper, we compare the energy efficient clustering-based protocols used in wireless sensor networks. The work involves implementation of homogeneous protocols, namely low-energy adaptive clustering hierarchy (LEACH), energy aware multi-hop multi-path hierarchical (EAMMH). Next, the heterogeneous protocols such as enhanced distributed energy efficient clustering (EDEEC) and stable election protocol (SEP) are executed. The analysis is carried out in terms of number of nodes and probability of election for cluster head (CH). The observations and results obtained for these protocols are presented.

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Authors and Affiliations

  1. Dayananda Sagar College of Engineering, Bengaluru, India

    Trupti Shripad Tagare

  2. Dayananda Sagar University, Bengaluru, India

    Rajashree Narendra

Authors
  1. Trupti Shripad Tagare
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  2. Rajashree Narendra
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Correspondence to Trupti Shripad Tagare .

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Editors and Affiliations

  1. Dean (R&D), CARE College of Engineering, Trichy, India

    A. Pasumpon Pandian

  2. Department of Electrical and Computer Engineering, Ryerson Communications Lab, Toronto, ON, Canada

    Xavier Fernando

  3. Go Perception Laboratory, Cornell University, Ithaca, NY, USA

    Wang Haoxiang

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Tagare, T.S., Narendra, R. (2022). Performance Analysis and Assessment of Various Energy Efficient Clustering-Based Protocols in WSN. In: Pandian, A.P., Fernando, X., Haoxiang, W. (eds) Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 117. Springer, Singapore. https://doi.org/10.1007/978-981-19-0898-9_11

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  • DOI: https://doi.org/10.1007/978-981-19-0898-9_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-0897-2

  • Online ISBN: 978-981-19-0898-9

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