Wireless Sensor Networks (WSNs) play a crucial role in monitoring
and gathering data from remote environments. Maximizing network
lifetime is paramount due to constrained sensor node energy. This
study addresses the challenge of efficient cluster head selection to
prolong network operation. The problem focuses on utilizing the Harris
Hawk Optimization (HHO) algorithm for selecting optimal cluster
heads in WSNs. HHO mimics the hunting behavior of Harris hawks to
iteratively refine the selection process, aiming to minimize energy
consumption while maintaining network coverage. The method
involves initializing Harris hawks (representing potential cluster
heads) within the sensor field, where their movements simulate search
and convergence towards optimal locations. Through computational
simulations, the effectiveness of HHO is evaluated against traditional
methods like LEACH and PSO. Results indicate that HHO outperforms
competitors by extending network lifetime up to 30%, with an average
reduction in energy consumption by 15%. Specifically, numerical
values show an increase in network lifetime from 3000 hours to 3900
hours, while reducing energy consumption from 2000 J/bit to 1700
J/bit. This research underscores the efficacy of HHO in enhancing
WSN efficiency through optimized cluster head selection, promising
sustainable operation in resource-constrained environments.
S. Mahima1, T. Kiruthiga2, B. Rajesh Kumar3, K. Kalaiselvan4, Hakeem Ahmed Othman5
Syed Ammal Arts and Science College, India1, Jai Shriram Engineering College, India2, Dhanalakshmi Srinivasan College of Engineering, India3, Roever Engineering College, India4, Albaydha University, Republic of Yemen5
Wireless Sensor Networks, Cluster Head Selection, Harris Hawk Optimization, Energy Efficiency, Network Lifetime
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| Published By :
ICTACT
Published In :
ICTACT Journal on Communication Technology
( Volume: 15 , Issue: 2 , Pages: 3185 - 3189 )
Date of Publication :
June 2024
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235
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