Enhanced Energy Efficient Clustering and Routing Algorithm in Wireless Sensor Network

Efficiency in energy consumption remains a critical concern in Wireless Sensor Networks due to their reliance on battery power. The major cause of this problem is the way Cluster Heads are chosen in clustering methods. This paper describes a custom- made Enhanced Energy Efficient Clustering and Routing protocol that can be used to solve these problems. The protocol has three steps which include; initially, application of k-means clustering technique to cluster nodes and select best CH nodes from each group, secondly designation of Super Cluster Head using Adaptive Neuro Fuzzy Inference System among CHs, and finally, determination of the most energy efficient multi path routing strategy for data transfer by utilizing Black Widow Optimization algorithm. Simulations results show that the proposed scheme outperforms other alternatives in terms of energy consumption, end-to-end latency and throughput. When compared with existing approaches, this method achieves a peak data rate of 23007 kbps with minimum energy consumption at 6 J as well as reduced delay time at 7.0533 ms.