A Chaotic Reptile Search Algorithm for Energy Consumption Optimization in Wireless Sensor Networks

A wireless sensor network (WSN) uses sensor nodes, which have an integrated processor for managing and monitoring the environment in a certain area. They are connected to the base station (BS), which functions as the central processing unit (CPU) of the WSN system. WSN has several difficulties, such as low processing power and a brief network lifespan. To solve the problem of network lifetime, we present a hybrid meta-heuristic (MH) optimization algorithm called the chaotic reptile search algorithm (CRSA) for energy conservation in WSNs. The proposed algorithm is an improvement on the original Reptile Search Algorithm (RSA) by combining the RSA algorithm and a chaotic map. RSA, like other meta-heuristic algorithms, suffers from trapping in local minima. Invoking the chaotic maps in the proposed algorithm can boost diversity and prevent becoming stuck in local minima. In the WSN, selecting the optimal cluster heads (CHs) helps save energy consumption. The proposed CRSA is used for selecting an optimum set of cluster heads amongst the other sensing nodes via the sensing field in a WSN. The experiments have evaluated the proposed algorithm under different conditions against five meta-heuristic algorithms and three versions of the low-energy adaptive clustering hierarchy (LEACH) algorithm. The proposed CRSA has verified the effectiveness of the mentioned algorithms in terms of the total consumed energy, the number of operating nodes, the packet reception by the base station, and the network lifetime. The findings of the experiment indicate that the suggested CRSA is a promising algorithm, and it achieves improvements against all these previously mentioned algorithms.