An ACO Algorithm for Effective Cluster Head Selection

TL;DR

This paper introduces an ant colony optimization algorithm for selecting minimal cluster heads in mobile ad hoc networks, aiming to reduce communication overhead and improve network performance.

Contribution

It combines four clustering schemes with ant colony optimization to effectively minimize the number of cluster heads in MANETs.

Findings

Algorithm effectively reduces number of cluster heads

Improves network performance and reduces overhead

Outperforms existing clustering methods

Abstract

This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.