Brief Announcement: Robust Self-stabilizing Construction of Bounded Size Weight-Based Clusters
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Robust self-stabilizing construction of bounded size weight-based clusters
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
Self-stabilization versus robust self-stabilization for clustering in ad-hoc network
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
W-PAC: an efficient weighted partitioning around cluster head mechanism for ad hoc network
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
From self- to self-stabilizing with service guarantee 1-hop weight-based clustering
SSS'12 Proceedings of the 14th international conference on Stabilization, Safety, and Security of Distributed Systems
Self-stabilizing k-hops clustering algorithm for wireless ad hoc networks
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Self-stabilizing with service guarantee construction of 1-hop weight-based bounded size clusters
Journal of Parallel and Distributed Computing
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Clustering means partitioning nodes into groups called clusters, providing the network with a hierarchical organization. A self-stabilizing protocol, regardless of the initial system state, automatically converges to a set of states that satisfy the problem specification without external intervention. Due to this property, self-stabilizing protocols are adapted to highly dynamic networks as ad hoc or sensors networks. In this paper, we propose a self-stabilizing clustering protocol. Our protocol guarantees a threshold (Size Bound) on the number of nodes that a clusterhead handle. Therefore, none of the clusterheads are overloaded at anytime. The criterion of the clusterheads election is based on their weight value, a general parameter that can be computed according to several node parameters as transmission power, battery power, ... .