An Enhanced Energy-Aware Cluster-Based Routing Algorithm in Wireless Sensor Networks

Abstract

Despite the wide improvement in wireless sensor networks, energy consumption is still considered as the most important challenge in this kind of network. Previous research studies have shown that a routing algorithm based on clustering could be a perfect solution to solve this problem. In this regard, an optimized routing algorithm based on consciously distribution of cluster heads and their load balancing has been suggested in this study. Initially, the network is divided into cells by the algorithm. Then, the genetic algorithm is used to determine the optimal number of nodes. In other words, after placement of the nodes in the environment, given that the base station is aware of the energy of remaining nodes, the chromosome length is set equal to the number of nodes that their residual energy in a specific area is greater than the average energy of neighboring nodes in the same specified area. Therefore, the chromosome length is reduced and we will move with a faster convergence in reaching the optimal solution. On the other hand, due to the low speed of the genetic algorithm in facing with larger networks after determining the cluster heads in each chromosome, those points are sent as initial points for the K-Means algorithm and this algorithm provides high-speed clustering process. Simulation results using NS2 tool showed that significant improvement has been achieved by using the proposed algorithm in increasing life time, throughput, residual energy and in decreasing delay of network compared to the two similar algorithms.