Abstract
To make up the deficiency of artificial intelligent ant colony algorithm in solving the clustering and path planning of wireless sensor network (WSN) a new random disturbance factor is proposed. A self-regulated random disturbance ant colony algorithm is obtained. An improved ant colony algorithm is proposed by combining the self-regulated random disturbance ant colony algorithm with chaos. After the algorithm improvement is completed, the improved artificial intelligent ant colony algorithm is applied to the cluster head fixed WSN node cluster and the path optimization process of each cluster head communication with the base station. The convergence speed, energy consumption and the survival time of the node cluster head are analyzed. The results show that the improved ant colony algorithm has good stability characteristics in the application and convergence of WSN. It can be seen that the improved ant colony algorithm is feasible in clustering and path planning of WSN.
Highlights
As one of the current hot topics in the field of bionic intelligent optimization and artificial intelligence, the artificial intelligence ant colony algorithm has strong robustness and convergence, and it is easy to fuse with other algorithms
In the wireless senor network (WSN) cluster routing scene, the application of improved ant colony algorithm is divided into two cases: when the cluster head node is fixed, the improved ant colony intelligent optimization algorithm is used to divide clusters
When the sensor node of the system is elected as cluster head, the improved ant colony intelligent optimization iJOE ‒ Vol 15, No 1, 2019
Summary
As one of the current hot topics in the field of bionic intelligent optimization and artificial intelligence, the artificial intelligence ant colony algorithm has strong robustness and convergence, and it is easy to fuse with other algorithms. The artificial intelligent ant colony algorithm with excellent performance and suitable for wireless senor network (WSN) clustering is selected, and the defects of ant colony algorithm are improved. In the WSN cluster routing scene, the application of improved ant colony algorithm is divided into two cases: when the cluster head node is fixed, the improved ant colony intelligent optimization algorithm is used to divide clusters. When the cluster head collects the data, the data is sent to the base station in a multi-hop way. At this time, the path planning of the information sending is implemented by the improved ant colony algorithm. When the sensor node of the system is elected as cluster head, the improved ant colony intelligent optimization iJOE ‒ Vol 15, No 1, 2019
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