Energy-Efficient Dynamic Clustering Protocol for Wireless Sensor Networks

developments in the sensor networks have made the researchers to find the energy efficient routing protocols. Sensor nodes are normally energy constrained and cannot be replaced in most cases. The need for energy efficiency in wireless sensor network is increasing considerably. This article proposed a new model to reduce the energy consumption by the sensor nodes. Our proposed model Energy Efficient Dynamic Clustering Protocol (EEDCP) distributes the energy consumption evenly among all sensor nodes to increase the life-time of the network. The simulation results show that the EEDCP outperforms its counterparts. consumption various techniques have been followed by the researchers. The sensor nodes are sensing data from the environment where they are deployed and send it to the Base Station which may be located far from the nodes. The sensors send the aggregated data to the sink either directly or multi- hop transmission. The energy is consumed in different levels when the transmission and reception. The energy consumption in transmission is more than the energy consumed for reception. The transmitters have the capacity to change their transmission power (5, 6). In case of single hop transmission, the sensors send the data directly to the sink base station. The nodes which are farther away from the base station have to spent more energy than the nodes which are nearer to the base station. The clustering approach is used to reduce the energy consumption. In the traditional clustering technique, the cluster-head nodes are fixed (7, 8, and 9). The nodes in the clusters send their data to the base station through the cluster- heads. The cluster head node transmits the aggregated data received from the member nodes. So the distance to be transmitted is reduced. But the node which is transmitting data to the base station will drain out its energy quickly. To avoid the quick drain of energy, the cluster-head nodes should be changed randomly. The modern clustering approaches facilitate the change of cluster-heads for each and every round. The cluster-head nodes can be self elected or elected based on certain factors, such as threshold value, residual energy, coverage efficiency, etc.