Wireless Sensor Networks Based on Genetic Algorithm

Advances in Wireless Sensor Network (WSN) technology have enabled the development of miniaturized, low-cost sensor nodes capable of sensing various physical/environmental conditions, data processing, and wireless communication. This technology has been widely applied in domains such as environmental monitoring, agriculture, and healthcare, enabling intelligent regional management. However, WSN characteristics - including limited transmission range, processing/storage capabilities, and energy resources of sensor nodes - necessitate more efficient data forwarding and processing methods. Consequently, WSN routing protocols play a crucial role in maintaining network routes and ensuring reliable multi-hop communication under these constraints. This paper provides a detailed investigation of WSN routing protocols and compares their advantages/limitations. In WSNs, routing protocols and cluster heads represent two key technologies. Routing protocols maintain network routes through algorithms like Dijkstra or A-star for path computation, while cluster heads manage local area communication and data processing using TDMA-based scheduling mechanisms. Designing efficient routing protocols and cluster head selection algorithms (e.g., LEACH protocol's random rotation or genetic algorithm-based optimization) remains a hot research topic in WSNs. Overall, the widespread applications of WSNs and their data processing/forwarding methods under special constraints constitute important research areas. Future work will continue exploring related technologies to enhance WSN performance and application scope, potentially implementing genetic algorithm optimizations in MATLAB using global optimization toolbox functions for population initialization, fitness evaluation, and selection operations.