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LOCI: Local Clustering Service for Large Scale Wireless Sensor Networks

By Vineet Mittal, Murat Demirbas and Anish Arora


We present a local, scalable, and fault-tolerant distributed clustering service, LOCI, that partitions a multi-hop wireless network into clusters of bounded physical radius [R; mR] where m is a constant greater than or equal to 2. That is, each cluster has a leader node such that all nodes within distance R of the leader belong to the cluster but no node beyond distance mR from the leader belongs to the cluster. LOCI is local in that each node only needs information about nodes that are at most distance 2R away. It is scalable in that each node maintains only a constant amount of state and completes its role in clustering in O(R4) time (O(R2) for a stronger system model), independent of the network size. It is fault-tolerant in that it is self-stabilizing in the presence of state corruption, node and link fail-stops, and node joins. The network partitions generated by LOCI form a Voronoi tessellation as each non-clusterhead node joins the cluster of the nearest clusterhead and the number of clusters LOCI yields is within a constant factor approximation of the minimum number of clusters theoretically feasible. Our simulations demonstrate that, for m = 2, the number of clusters constructed by LOCI exceed the minimum number of clusters theoretically feasible only by a factor of 1.5 for a 1-D network and 2.3 for a 2-D network. As hierarchical clustering is readily achieved by instantiating LOCI at multiple levels, LOCI provides a framework for scalable and fault-tolerant distributed tracking structure for pursuer-evader scenarios that has arisen in our recent work in sensor networks. Furthermore, as part of our efforts towards developing sensor network services in the DARPA Network Embedded Software Technology (NEST) program, we have implemented LOCI in TinyOS on the Mica2 mote platform

Year: 2009
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