Lifetime Maximization Using Grey Wolf Optimization Routing Protocol with statistical Technique in WSNs

Authors

  • Baida'a Abdul Qader Khudor Department of Computer Science, College of Computer Science and Information Technology, University of Basrah, Basrah, IRAQ
  • Dheyaa Mezaal Hussein University of Technology Office of the President of the University
  • Yousif Abdulwahab Kheerallah Department of Computer Technology Engineering, Shatt Al-Arab University College, Basra, Iraq
  • Jawad Alkenani Department of Computer Science, Shatt Al-Arab University College, Basra, Iraq
  • Imad S. Alshawi Department of Computer Science, College of Computer Science and Information Technology, University of Basrah, Basrah, IRAQ

DOI:

https://doi.org/10.31449/inf.v47i5.4601

Abstract

Generally, the greatest issue in Wireless Sensor Networks (WSNs) is to make sensor nodes powered by low-cost batteries with limited power last as long as feasible. Thus, energy conservation is an essential topic in WSNs. Since wireless data transmission consumes a substantial amount of energy, the routing mechanism plays a crucial role in preserving the available energy. Consequently, energy-efficient routing methods may save battery power and extend the network's lifespan. Using complicated protocols to properly design data routing may save energy use, but may cause processing delays. This paper offers the Grey Wolf Optimization Routing Protocol (GWORP), extended by using a select optimal path method with detects the statistical best value novel routing mechanism. It is used to discover the ideal route from the source node to the destination (sink) and reuse that path in a manner that ensures energy consumption is evenly distributed across the nodes of a WSN while lowering the time required to find the routing path from scratch each time. Interestingly, GWORP was shown to be more effective than the PSORP (Particle Swarm Optimization Routing Protocol) algorithm in terms of lowering energy usage and minimizing end-to-end latency. The findings also indicate that the network lifespan attained by GWORP might be about 73% longer than that achieved by PSORP.

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Published

2023-05-23

How to Cite

Khudor, B. A. Q., Hussein, D. M., Kheerallah, Y. A., Alkenani, J., & Alshawi, I. S. (2023). Lifetime Maximization Using Grey Wolf Optimization Routing Protocol with statistical Technique in WSNs. Informatica, 47(5). https://doi.org/10.31449/inf.v47i5.4601

Issue

Vol. 47 No. 5 (2023): Online-only issue

Section

Online-only

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