An energy-efficient and density -aware clustering for WSNs
A. A. Khamiss, Senchun Chai, Baihai Zhang, Jingye Luan, Li Qiao · 2014
Wireless Sensor Networks are sets of thousands or more of sensor nodes with very small size and limited energy, scattered over particular area to sense a certain physical phenomenon. Energy constraints are the most important challenge for these networks to work efficiently for long time. Most existing clustering algorithms are applied without considering the density of region. In this paper, density-aware clustering algorithm that based on region density and uses fuzzy clustering technique in cluster formation is proposed .The cluster head selection method depends on intra and inter-communication distances in addition to residual energy. It is cluster-based, centralized, single-hop routing method. The simulation results show that the algorithm can balance the energy load between nodes, reduce energy consumption and prolong the stability period and life time of network compared to traditional LEACH-C.