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Metaheuristic-Enabled Shortest Path Selection for IoT-Based Wireless Sensor Network

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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 66))

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Abstract

IoT is defined as a pervasive and global network that aids and provides the system for monitoring and controlling the physical world through the processing and analysis of generated data by IoT sensor devices. Wireless sensor networks (WSNs) are comprised of a large number of nodes distributed in a vast region. Routing protocols are responsible for the development and the management of network routes. This paper intends to propose an optimized routing model for selecting the optimal shortest path in IoT-based WSN. More particularly, a dragonfly algorithm with Brownian motion (DABR) model is introduced to select the optimal route by taking into consideration of certain constraints such as (i) delay (ii) distance (iii) packet drop rate (PDR) and (iv) energy. Finally, the performance of the proposed work is compared with the conventional models to demonstrate the superior performance.

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Author information

Authors and Affiliations

  1. Working for UST, Europe, UK

    Subramonian Krishna Sarma

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  1. Subramonian Krishna Sarma
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Correspondence to Subramonian Krishna Sarma .

Editor information

Editors and Affiliations

  1. Department of CSE, KGiSL Institute of Technology, Coimbatore, India

    A.Pasumpon Pandian

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

    Xavier Fernando

  3. Edith Cowan University (ECU), Joondalup, WA, Australia

    Syed Mohammed Shamsul Islam

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Sarma, S.K. (2021). Metaheuristic-Enabled Shortest Path Selection for IoT-Based Wireless Sensor Network. In: Pandian, A., Fernando, X., Islam, S.M.S. (eds) Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 66. Springer, Singapore. https://doi.org/10.1007/978-981-16-0965-7_8

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  • DOI: https://doi.org/10.1007/978-981-16-0965-7_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0964-0

  • Online ISBN: 978-981-16-0965-7

  • eBook Packages: EngineeringEngineering (R0)

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