An Energy Efficient and Density control Clustering Algorithm for Wireless Sensor Network
Meriem Meddah, Rim Haddad, Tahar Ezzedine · 2017
In order to extend the lifetime of wireless sensor networks, many approaches have been done dividing the network into clusters, gathering data from nodes and aggregating them to the base station. Some of the clustering algorithms consider the residual energy of the nodes in the selection of the cluster heads and others rotate the selection of cluster heads periodically. However, they rarely study the density of the network or the local distance. In this paper, we introduce an energy efficient and density control clustering algorithm (EEDCA) which chooses the best nodes in the network to become cluster heads then divides the network into clusters. On this proposed approach, the selection of the cluster head depends on residual energy, density and distance. Each node compares its residual energy with nodes placed on its range. The EEDCA algorithm extends the lifetime of the wireless sensor network, and to prove its efficiency our simulation results show that the proposed solution aims to prolong the lifetime of the wireless sensor network more efficiently.