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A Grey Wolf Optimization Approach for Improving the Performance of Wireless Sensor Networks

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Abstract

Optimizing the energy consumption of sensor nodes have been a big design issue in wireless sensor networks (WSNs). Energy efficient WSN usually compromise with network stability which is a crucial factor in ensuring full, lasting and reliable coverage of the network. Connected dominating set (CDS) based virtual backbone and traditional cluster based approach are two most commonly used data delivery protocols in a WSN. The paper proposes a distance based stable connected dominating set methodology using a meta-heuristic algorithm grey wolf optimization (DBSCDS-GWO) for achieving a stable, balanced and energy efficient CDS based WSN. We also propose a distance based stable clustering algorithm using GWO (DBSC-GWO) for improving the performance of cluster based WSN. DBSCDS-GWO performs better than RMCDS-GA and SAECDS-GA by 70.5% and 67.7% respectively and DBSC-GWO performs better than LEACH and DRESEP by 74.7% and 50.6% respectively in terms of both network stability and energy efficiency. Performance of the proposed algorithm is validated using Matlab simulation and Netsim Emulator.

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Abbreviations

SN:

Sensor node

WSN:

Wireless sensor network

CDS:

Connected dominating set

GWO:

Grey wolf optimization

DBSCDS-GWO:

Distance based stable connected dominating set methodology using GWO

DBSC-GWO:

Distance based stable clustering algorithm using GWO

RMCDS-GA:

Reliable minimum CDS using Genetic algorithm

SAECDS-GA:

Stability aware evolutionary CDS using GA

LEACH:

Low energy adaptive clustering hierarchy

VB:

Virtual backbone

DS:

Dominating set

G (V, E):

Graph (vertices, edges)

CH:

Cluster head

mCDS:

Minimum size CDS

ACO:

Ant colony optimization

LBCDS-GA:

Load-balanced CDS construction using GA

LEACH-C:

LEACH-Centralized

IPI:

Inheritance population initialization

FDN, HDN, LDN:

First, half and last dead node

IoT:

Internet of Things

IoE:

Internet of Everything

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Acknowledgements

We acknowledge the contribution of undergraduate student Gayatri K.V.R in this work.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Delhi Technological University, Delhi, India

    Ajay Kaushik & Daya Gupta

  2. Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India

    S. Indu

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  1. Ajay Kaushik
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Correspondence to Ajay Kaushik.

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Kaushik, A., Indu, S. & Gupta, D. A Grey Wolf Optimization Approach for Improving the Performance of Wireless Sensor Networks. Wireless Pers Commun 106, 1429–1449 (2019). https://doi.org/10.1007/s11277-019-06223-2

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