A self-stabilizing O(n)-round k-clustering algorithm
Given an arbitrary network G of processes with unique IDs and no designated leader, and given a k-dominating set I ⊆ G, we propose a silent selfstabilizing distributed algorithm that computes a subset D of I which is a minimal k-dominating set of G. Using D as the set of clusterheads, a partition of G into clusters, each of radius k, follows. The algorithm is comparison-based, requires O(log n) space per process, converges in O(n) rounds and O(n2) steps, where n is the size of the network, and works under an unfair scheduler.
Datta, A. K.,
Larmore, L. L.
A self-stabilizing O(n)-round k-clustering algorithm.
28th IEEE International Symposium on Reliable Distributed Systems, 2009