Wireless Ad-hoc networks are distributed systems that often reside in error-prone environments. Self-stabilization lets the system recover autonomously from an arbitrary system state, making the system recover from errors and temporarily broken assumptions. Clustering nodes within ad-hoc networks can help forming backbones, facilitating routing, improving scaling, aggregating information, saving power and much more. We present a self-stabilizing distributed (k,r)-clustering algorithm. A (k,r)-clustering assigns k cluster heads within r communication hops for all nodes in the network while trying to minimize the total number of cluster heads. The algorithm assumes a bound on clock frequency differences and a limited guarantee on message delivery. It uses multiple paths to different cluster heads for improved security, availability and fault tolerance. The algorithm assigns, when possible, at least k cluster heads to each node within O(rπλ 3) time from an arbitrary system configuration, where π is a limit on message loss and λ is a limit on pulse rate differences. The set of cluster heads stabilizes, with high probability, to a local minimum within O(rπλ 4 glogn) time, where n is the size of the network and g is an upper bound on the number of nodes within 2r hops. © 2012 Springer-Verlag.
CITATION STYLE
Larsson, A., & Tsigas, P. (2012). Self-stabilizing (k,r)-clustering in clock rate-limited systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7355 LNCS, pp. 219–230). https://doi.org/10.1007/978-3-642-31104-8_19
Mendeley helps you to discover research relevant for your work.