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Energy Proficient Reduced Coverage Set with Particle Swarm Optimization for Distributed Sensor Network

T. V. Chithra1,*, A. Milton2

1 Department of Computer Science and Engineering, Arunachala College of Engineering for Women, Manavilai, Tamil Nadu, 629203, India
2 Department of Electronics and Communication Engineering, St. Xavier’s Catholic College of Engineering, Chunkankadai, Tamil Nadu, 629003, India

* Corresponding Author: T. V. Chithra. Email: email

Computer Systems Science and Engineering 2023, 45(2), 1611-1623. https://doi.org/10.32604/csse.2023.026561

Abstract

Retransmission avoidance is an essential need for any type of wireless communication. As retransmissions induce the unnecessary presence of redundant data in every accessible node. As storage capacity is symmetrical to the size of the memory, less storage capacity is experienced due to the restricted size of the respective node. In this proposed work, we have discussed the integration of the Energy Proficient Reduced Coverage Set with Particle Swarm Optimization (PSO). PSO is a metaheuristic global search enhancement technique that promotes the searching of the best nodes in the search space. PSO is integrated with a Reduced Coverage Set, to obtain an optimal path with only high-power transmitting nodes. Energy Proficient Reduced Coverage Set with PSO constructs a set of only best nodes based on the fitness solution, to cover the whole network. The proposed algorithm has experimented with a different number of nodes. Comparison has been made between original and improved algorithm shows that improved algorithm performs better than the existing by reducing the redundant packet transmissions by 18% ~ 40%, thereby increasing the network lifetime.

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Cite This Article

T. V. Chithra and A. Milton, "Energy proficient reduced coverage set with particle swarm optimization for distributed sensor network," Computer Systems Science and Engineering, vol. 45, no.2, pp. 1611–1623, 2023. https://doi.org/10.32604/csse.2023.026561



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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