Research on Routing Planning of Wireless Sensor Networks Based on Cat Swarm Optimization Algorithm

In the wireless sensor network, the sensor node is not charged by the micro-battery, which makes the network energy limited and the topology is unstable. Therefore, it is designed to ensure the stability of the network while finding a balance on the basis of energy balance. A routing algorithm that senses the routing path between a node and a sink node or base station is necessary. Cat Swarm Optimization (CSO) is a new clustering intelligent algorithm. It is aimed at the shortcomings of cat group algorithm in wireless sensor network routing applications, such as easy to fall into local optimum and slow convergence. An improved cat group algorithm. There are two improvements. One adjusts the grouping rate of the cat group mode with time, accelerates the convergence speed of the cat group algorithm, and finds the optimal path faster. Secondly, the inertia weighting factor is introduced in the tracking mode to avoid the optimal solution falling into the local part. Optimal and balanced energy consumption. The simulation experiment of the proposed routing algorithm is carried out by NS2 (Network Simulator-version2) simulator. The experimental results show that the improved algorithm converges faster and the convergence speed is increased by about 20% compared with that before the improvement. Factor, the search ability is stronger, can avoid falling into local optimum, the average residual energy of the improved node is higher and the residual energy standard deviation is less than before the improvement, indicating that the improved energy consumption is more balanced, and can extend the life cycle of the network and improve the cat population. The performance of the algorithm is better than the basic cat group algorithm. In the contrast experiment, the directional diffusion routing algorithm is added. The initial energy of the node is 500 energy units. The average residual energy of the cat group optimization algorithm is 320 energy units higher than the 200 energy units of the directed diffusion routing, indicating that the cat group optimization algorithm can Better extend the life of wireless sensor networks. The experimental results show that the cat group optimization algorithm can better balance the energy consumption of wireless sensor network nodes, prolong the network lifetime and improve the stability of the network.