Lifetime Maximization Using Grey Wolf Optimization Routing Protocol with statistical Technique in WSNs
The main challenge in Wireless Sensor Networks (WSNs) is to maximize the lifespan of sensor nodes powered by low-cost batteries with limited power. Energy conservation is crucial, and routing mechanisms play a vital role in preserving energy. Energy-efficient routing methods can save battery power a...
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Veröffentlicht in: | Informatica (Ljubljana) 2023, Vol.47 (5), p.75-81 |
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description | The main challenge in Wireless Sensor Networks (WSNs) is to maximize the lifespan of sensor nodes powered by low-cost batteries with limited power. Energy conservation is crucial, and routing mechanisms play a vital role in preserving energy. Energy-efficient routing methods can save battery power and extend the network's lifespan. This study introduces the Grey Wolf Optimization Routing Protocol (GWORP), enhanced with a novel routing mechanism that detects the statistically optimal path. It enables the discovery and reuse of an ideal route from the source to the destination, ensuring balanced energy consumption across WSN nodes and reducing path discovery time. GWORP outperforms the PSORP (Particle Swarm Optimization Routing Protocol) algorithm, significantly reducing energy usage and minimizing end-to-end latency. The findings suggest that GWORP could potentially increase the network lifespan by approximately 73% compared to PSORP. |
doi_str_mv | 10.31449/inf.v47i5.4601 |
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subjects | Algorithms Communication Computer networks Data transmission Energy conservation Energy consumption Heuristic Internet of Things Life span Linear programming Network latency Nodes Optimization techniques Particle swarm optimization Power management Protocol Quality of service Routing (telecommunications) Sensors Wireless sensor networks |
title | Lifetime Maximization Using Grey Wolf Optimization Routing Protocol with statistical Technique in WSNs |
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