An Energy-Aware Hybrid GA-PSO Routing Protocol for Solar-Harvesting Wireless Sensor Networks in Smart Cities

Abstract

Energy-harvesting wireless sensor networks (EHWSNs) play a critical role in providing a sustainable infrastructure in smart cities. Nevertheless, ensuring continuous operation is still difficult owing to the intermittent nature of solar irradiance and suboptimal routing structures. Existing schemes like M-LEACH make use of probability-based clustering and hence result in large disparities in energy consumption, leading to premature failure of some nodes. To solve this problem, this work proposes a new energy-aware hybrid routing scheme that makes use of the combination of Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Herein, GA explores the search space to obtain an elite set of diverse routing schemes whereas the PSO is responsible for fine-tuning the obtained routing schemes to ensure minimal delay in communication and maximization of the use of the solar energy. The performance of the proposed scheme was analyzed based on hourly solar irradiance values collected from the NSRDB of 2019 in Iraq for 90 days of winter season. From a set of 50 independent Monte Carlo simulations, the proposed hybrid scheme increases the lifetime of the system by 2.13× over that of Pure GA and by 1.89× over that of M-LEACH. In addition, the proposed hybrid protocol ensures nearperfect packet delivery rate along with higher energy efficiency, resulting in more than 95% node survival at the end of the simulation period.