Efficient clustering and energy optimization algorithm for WSNs: An approach in environment monitoring system

In recent progress in Wireless Sensor Networks (WSNs) has been developing into one of the main attractive networking technologies, as it can be deployed without communication structures. A sensor network is composed of a number of sensor nodes which are responsible for regulation of the physical experience and transmission of the periodical results to the BS (base station). Consequently, minimize the energy consumption and extend the network lifetime are the key challenges in wireless networks. In this aspect, we proposed a hierarchical clustering method algorithm, PESCA (Position Energy Spectral Cluster Algorithm) that determine the number of clusters in a network automatically, depending on residual energy and BS distance. The idea of this clustering scheme is to modify the k-means algorithm and proposes new features of the network nodes .In addition, we present a distance-energy cluster structure algorithm (DECSA) based on the classic clustering algorithm LEACH. The experiments results show that the proposed algorithm presents a significant performance improvement in terms of energy and efficient clustering.