Energy Efficient Weighted Clustering Algorithm in Wireless Sensor Networks
With the advancement in communication and internet technologies, recently there have been many research efforts in the area of Wireless Sensor Networks (WSNs) to conserve energy. Clustering mechanisms have been applied to WSNs to enhance the network performance while reducing the necessary energy consumption. The goal of Weighted Clustering Algorithm (WCA) is to determine the cluster heads dynamically based on a combined weight metric that includes one or more parameters such as node degree, distances with respect to a nodes neighbors, node speed and the time spent as a cluster head. In this work, we have proposed a refined and improved version of WCA known as Energy Efficient Weighted Clustering Algorithm (EEWCA) to prolong the network lifetime by reducing energy consumption. EEWCA is designed and simulated with additional constraint on energy for the selection of cluster heads. Both the WCA and EEWCA schemes have been simulated using MATLAB. The proposed EEWCA behaves better than WCA for longer system lifetime. The proposed work is simulated and performance is tested for number of clusters and average execution time. Simulation results show that the EEWCA outperforms WCA in terms of both the number of clusters formed and the execution time.
