Hybrid Chaotic Salp Swarm with Crossover Algorithm for Underground Wireless Sensor Networks

Abstract

Resource management in Underground Wireless Sensor Networks (UWSNs) is one of the pillars to extend the network lifetime. An intriguing design goal for such networks is to achieve balanced energy and spectral resource utilization. This paper focuses on optimizing the resource efficiency in UWSNs where underground relay nodes amplify and forward sensed data, received from the buried source nodes through a lossy soil medium, to the aboveground base station. A new algorithm called the Hybrid Chaotic Salp Swarm and Crossover (HCSSC) algorithm is proposed to obtain the optimal source and relay transmission powers to maximize the network resource efficiency. The proposed algorithm improves the standard Salp Swarm Algorithm (SSA) by considering a chaotic map to initialize the population along with performing the crossover technique in the position updates of salps. Through experimental results, the HCSSC algorithm proves its outstanding superiority to the standard SSA for resource efficiency optimization. Hence, the network's lifetime is prolonged. Indeed, the proposed algorithm achieves an improvement performance of 23.6% and 20.4% for the resource efficiency and average remaining relay battery per transmission, respectively. Furthermore, simulation results demonstrate that the HCSSC algorithm proves its efficacy in the case of both equal and different node battery capacities.