Recently wireless sensor network (WSN) has become one of the most interesting networking technologies, since it can be deployed\nwithout communication infrastructures. A sensor network is composed of a large number of sensor nodes; these nodes are\nresponsible for supervision of the physical phenomenon and transmission of the periodical results to the base station. Therefore,\nimproving the energy efficiency and maximizing the networking lifetime are the major challenges in this kind of networks. To deal\nwith this, a hierarchical clustering scheme, called Location-Energy Spectral Cluster Algorithm (LESCA), is proposed in this paper.\nLESCA determines automatically the number of clusters in a network. It is based on spectral classification and considers both the\nresidual energy and some properties of nodes. In fact, our approach uses the K-ways algorithm and proposes new features of the\nnetwork nodes such as average energy, distance to BS, and distance to clusters centers in order to determine the clusters and to\nelect the cluster�s heads of aWSN. The simulation results show that if the clusters are not constructed in an optimal way and/or the\nnumber of the clusters is greater or less than the optimal number of clusters, the total consumed energy of the sensor network per\nround is increased exponentially.
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