A Genetic Algorithm with Self-Configuration Chromosome for the Optimization of Wireless Sensor Networks
Trong-The Nguyen, Chin‐Shiuh Shieh, Mong‐Fong Horng, Thi-Kien Dao · 2014
In typical applications of sensor networks, unattended sensors are randomly deployed. It is essential to endow sensor networks with self-organization ability in order to achieve optimal performance in terms of operational lifetime. This task could be even more challenging when sensor nodes are far away from the sink node, since the long communication range can drain out the energy of sensors quickly and reduce the lifetime of a network considerably. In this paper, a new approach based on genetic algorithm with self-configuration chromosome is applied in the cluster formation of a sensor network. It is designed to cluster sensors into a number of independent clusters, such that the total communication distances can be minimized, and therefore prolong the network lifetime. Search strategy to select cluster heads for an internal structure optimized network design relying on Genetic algorithm (GA) and exploiting on evolutionary approach for the computation of optimal distributed deployment is presented. Experimental results show that the proposed approach outperforms in both solution quality and convergence speed.