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The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is base don network energy maps and Quality-of-Service (QoS) requirements. The clustering problem is mode ledasa hyper graph partitioning and its resolution is based on a tabu search heuristic. The authors' approach defines moves using largest size cliques in a feasibility cluster graph. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that their tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach issue table for handling network extensibility in a satisfactory manner.
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