Energy Distance Clustering Algorithm (EDCA) for Wireless Sensor Networks

In this paper, we proposed a novel clustering approach for data transmission. The proposed method improves the lifetime of Wireless Sensor Network (WSN). In this clustering method we have considered the remaining energy of sensor node and the distance between sensor node to the sink as the key factor for selecting Cluster Head (CH). Because we have considered distance from sink to the sensor node, hence proposed clustering approach is able to solve the hotspot problem, which is the major issue in WSN. We have taken remaining energy as the leading factor, so we get better result with respect to the consumption of energy for transmission of data from sensor nodes to the base station. Most of the proposed models are focused only on the remaining energy of the node, but in this approach we have considered energy as well as distance for improving the data transmission efficiency in the WSN. In this paper we have introduced a clustering approach to select the Cluster Head, after that all nearest nodes become the member of the selected Cluster Head. All the sensor nodes send data to their CH and then CH send all the collected data to the sink node directly. Cluster Head changes in each round and the clusters also change in each round, but the process for selecting CH and forwarding the data to the sink, remain the same for all the rounds. We have compared our result with the random clustering algorithm in three different scenarios, the results show that our proposed model provides better results in all the scenarios.