Farmland WSN Routing Optimization Method Based on Improved Particle Swarm Optimization - MIAO Yisheng, ZHAO Chunjiang, WU Huarui (Jisuanji gongcheng, 2022)
The application environment of a farmland Wireless Sensor Network(WSN) is complex.The factors affecting network transmission include environmental variables, crop growth, etc.The routing protocol is an important link in the network data collection process.Therefore, research activities focused on energy consumption optimization for farmland WSN has garnered increased attention recently.Most traditional energy consumption optimization routing algorithms are designed for static network environments, which are difficult to apply to dynamic farmland monitoring scenarios.Therefore, we propose a routing optimization algorithm, namely, RD-PSO, based on improved Particle Swarm Optimization(PSO) in this study.Different routing transmission paths are abstracted as particles, and the fitness function is constructed according to the key factors, such as farmland network energy consumption, residual energy, network transmission hops, and link quality, to improve the environmental adaptability of path optimization.Furthermore, aiming to improve the low iterative efficiency of PSO routing during random initialization, a reverse detection method is used to determine the initialization topology position of the network nodes, shorten the distance between the initial position and optimal solution, and improve the convergence speed of the algorithm.The experimental results demonstrate that compared with ELMR, EEABR, and MR-PSO routing algorithms, RD-PSO attains a faster convergence speed and better performance in network life cycle, energy consumption balance effect, and average transmission hops.These developments ensure that the adaptability of our routing algorithm is superior in the dynamic environment of farmland compared with the existing methods.