Overlapping Multihop Clustering for Wireless Sensor Networks

Abstract

Clustering is a standard approach for achieving efficient and scalable\nperformance in wireless sensor networks. Traditionally, clustering algorithms\naim at generating a number of disjoint clusters that satisfy some criteria. In\nthis paper, we formulate a novel clustering problem that aims at generating\noverlapping multi-hop clusters. Overlapping clusters are useful in many sensor\nnetwork applications, including inter-cluster routing, node localization, and\ntime synchronization protocols. We also propose a randomized, distributed\nmulti-hop clustering algorithm (KOCA) for solving the overlapping clustering\nproblem. KOCA aims at generating connected overlapping clusters that cover the\nentire sensor network with a specific average overlapping degree. Through\nanalysis and simulation experiments we show how to select the different values\nof the parameters to achieve the clustering process objectives. Moreover, the\nresults show that KOCA produces approximately equal-sized clusters, which\nallows distributing the load evenly over different clusters. In addition, KOCA\nis scalable; the clustering formation terminates in a constant time regardless\nof the network size.\n