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|Title:||On the Optimality of Non-Uniform Clustering in Wireless Sensor Networks|
|Keywords:||energy-efficiency, clustering, data correlation, wireless sensor networks|
|Abstract:||In wireless sensor networks, cluster-based data gathering has been pursued as a means to achieve network scalability as well as energy efficiency. By dividing a network into clusters, data aggregation and compression can be conveniently implemented in each cluster resulting in significant reduction in overall network energy consumption. Although many clustering algorithms have been proposed in the literature for minimizing energy consumption in sensor networks, a comprehensive and systematic analysis of optimal clustering subject to inherent network attributes such as data correlation, node density, and distance to the sink is still lacking. In particular, existing clustering schemes are designed to form uniform clusters in the network, where, on average, clusters have the same size. In this paper, we exploit spatial data correlation present among sensor readings to form optimal-sized clusters that minimize the total energy cost of the network. We develop a generalized multi-region network model that captures the interplay between clustering and data correlation, and postulate that a heterogeneous clustering scheme, with larger clusters at further distances from the sink, is more energy-efficient than uniform clustering. Based on this model, we develop a distributed randomized clustering algorithm that generates optimal-sized non-uniform clusters throughout the network. Simulation results confirm the superiority of our novel algorithm against uniform clustering schemes.|
|Appears in Collections:||Ghaderi, Majid|
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