Automatic Distance Adaption for Dominating Set-Based Clustering in Wireless Mesh Networks

This paper proposes an automatic adaptive k-distance dominating set-based clustering scheme for service discovery in Wireless Mesh Networks. Supernodes and clients form a so-called virtual backbone where clients are at most k hops away from a supernode. The scheme automatically adapts the hop distance between supernodes and clients based on stability metrics to reduce re-clustering situations. We propose a collaboration algorithm, where each node tries to increase its distance value k as long as the stability of the potentially covered k-neighborhood is increasing and does not affect the stability of neighbor nodes. The measurements are performed in our wireless mesh testbed.