Low Energy-Efficient Clustering and Routing Based on Genetic Algorithm in WSNs
To accommodate the limited resources of sensors and specially energy capacity, researchers are increasingly interested in their improvement by developing new aware energy protocols to relay data to the concerned application. Finding near optimal solutions for the energy problem is still an issue in Wireless Sensor Networks (WSNs). A new era is opened with algorithms inspired by nature, which are meta-heuristic imitating living systems, to solve optimization problems. For this purpose, the Low Energy-Efficient Clustering and Routing Based on Genetic Algorithm (LECR-GA) mechanism is proposed. LECR-GA aims to prolong the WSN life-time and enhance its quality of service (QoS). Extensive simulations of the proposed solution were performed and their results were compared with those of literature.
KeywordsWireless Sensor Networks Bio-inspired Genetic algorithm Clustering Routing
This research work is supported in part by PHC-Tassili, Grant Number 18MDU114.
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