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Clustering is a fundamental performance improvement technique in wireless sensor networks, which can increase network scalability, lifetime and power level. In this paper, the authors integrate the multi-hop technique with a backup-based clustering algorithm using the residual energy to organize sensors. By using an adaptive backup strategy as well as the residual energy, the algorithm not only realizes load balance among sensor node, but also achieves dynamic cluster head distribution across the network in a timeout manner. Simulation results also demonstrate their algorithm is more energy-efficient compared to other algorithms. Their algorithm is also easily extended to avoid the formation of forced cluster heads, thereby it achieves better network management, energy-efficiency and scalability.
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