A Self-Stabilizing O(k)-Time k-Clustering Algorithm

Authors:
Ajoy K. Datta;Lawrence L. Larmore;Priyanka Vemula
Affiliations:
-;-;-
Venue:
The Computer Journal
Year:
2010

Citing 0
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Abstract

A silent self-stabilizing asynchronous distributed algorithm is given for constructing a k-dominating set, and hence a k-clustering, of a connected network of processes with unique IDs and no designated leader. The algorithm is comparison-based, takes O(k) time and uses O(k log n) space per process, where n is the size of the network. It is known that finding a minimum k-dominating set is NP-hard. A lower bound is given, showing that any comparison-based algorithm for the k-clustering problem that produces clusters of average size more than 2 in the worst case takes Ω(diam) time, where diam is the diameter of the network.