WACA: A Hierarchical Weighted Clustering Algorithm optimized for Mobile Hybrid Networks

TL;DR

This paper introduces WACA, a hierarchical weighted clustering algorithm designed for mobile hybrid networks that minimizes unnecessary clusterhead re-elections by considering stability criteria without relying on geographical data.

Contribution

The paper proposes a novel localized clustering algorithm that reduces re-election frequency in mobile ad-hoc networks by using stability-based weighted criteria, avoiding the need for geographical information.

Findings

Reduces clusterhead re-elections in mobile networks

Operates without geographical or speed data

Enhances stability of network clusters

Abstract

Clustering techniques create hierarchal network structures, called clusters, on an otherwise flat network. In a dynamic environment-in terms of node mobility as well as in terms of steadily changing device parameters-the clusterhead election process has to be re-invoked according to a suitable update policy. Cluster re-organization causes additional message exchanges and computational complexity and it execution has to be optimized. Our investigations focus on the problem of minimizing clusterhead re-elections by considering stability criteria. These criteria are based on topological characteristics as well as on device parameters. This paper presents a weighted clustering algorithm optimized to avoid needless clusterhead re-elections for stable clusters in mobile ad-hoc networks. The proposed localized algorithm deals with mobility, but does not require geographical, speed or distances information.