Genetic Algorithm Based Energy Efficient Cluster Head Selection and Cluster Formation and Establishment for Hierarchical Wireless Sensor Networks
Keywords:
Wireless Sensor Network, Genetic Algorithm, ClusteringAbstract
Wireless Sensor Networks (WSN) emerged due to advancements of wireless communication, Micro Electro Mechanical Systems (MEMS) etc. which plays a vital role in certain critical real world applications. In WSN, energy consumption is an important issue that is to be addressed to improve network life time and stability. Rather than other medium, sensor nodes are utilized for data transmission in WSN. Sensor nodes form ad hoc network to gather and transmit information to sink (or) to the destination node. Clustering plays vital role in the energy consumption of the sensor network, where the clustering technique improves the energy efficiency of the network compared to flat architecture. But the balanced load over the each cluster is not considered in many algorithms. In this paper, a novel hybrid technique is proposed to form clustering based on Genetic Algorithm (GE) and a hierarchical technique Algorithm for Cluster Establishment (ACE), where the establishment of optimal clustering is carried out based on selection of Cluster Head (CH) node. The CH selection is carried out based on the computation of novel fitness value of each node based on energy, distance and number of alive nodes. The CH selection is implemented by considering only the number of alive nodes in each round with their residual energy as a parameter with feedback mechanism. NS2 simulator is used to evaluate the performance of this method in terms of residual energy, energy dissipation, number of an alive nodes and number of packets delivered to CH and to Base Station (BS). Simulation results reveal that our proposed hybrid technique outperforms LEACH in terms of energy conservation and network lifetime.
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