Clustering and path planning for wireless sensor networks based on improved ant colony algorithm

13Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Fang, J. (2019). Clustering and path planning for wireless sensor networks based on improved ant colony algorithm. International Journal of Online and Biomedical Engineering, 15(1), 129–142. https://doi.org/10.3991/ijoe.v15i01.9784

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free