An Energy-Efficient Clustering Method Based on Butterfly Optimization Algorithm by Considering the Criterion of Intra-cluster Distances in WSNs

Wireless sensor networks (WSNs) are crucial for monitoring events, but limited energy from sensor nodes reduces network lifetime. Hierarchical routing, particularly clustering, effectively manages energy consumption and increases network lifetime. This paper proposes a clustering method utilizing the Butterfly Optimization Algorithm and considering the intra-cluster distances as a new objective in the fitness function. In the proposed method, the objectives of the standard deviation of intra-cluster distances and cluster members' number along with other objectives such as distance between a node and the base station and node residual energy, are considered a new fitness function. This method is simulated with MATLAB in two scenarios (base station is located in the center and outside of the environment). The results of the first scenario show that the death of the first node is 1.06 times, the energy consumption is 1.12%, and the standard deviation of the number of cluster nodes is 38.50% better compared with base-method. In addition, the results of the second scenario for the same criteria are 6.16 times, 15.38%, and 48.28% better in comparison with the base-method, respectively.