Clustering and Path Planning for Wireless Sensor Networks Based on Improved Ant Colony Algorithm

Jiajuan Fang

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.

Keywords


ant colony algorithm; wireless sensor network; path planning

Full Text:

PDF



International Journal of Online and Biomedical Engineering (iJOE).ISSN: 2626-8493
Creative Commons License
Indexing:
Web of Science ESCI logoINSPEC logo DBLP logo ELSEVIER Scopus logo EBSCO logo Ulrich's logoGoogle Scholar logo Microsoft® Academic Search