A New Data Gathering Algorithm Based on Mutual Supportability and Grey Prediction in Wireless Sensor Networks

The energy of node in Wireless Sensor Networks (WSN) is severely constrained, it is very important to maximize the network lifetime by reducing the data dissemination among the nodes. In order to enhance energy efficiency and prolong the system lifetime, a novel data gathering algorithm based on mutual supportability and grey prediction is presented. According to of nodes´ the historical data, cluster heads make the decision which nodes are redundant, and then predict some data of these redundant nodes. In order to improve precision of the fused data, the mutual supportability of nodes and the parameter of the grey mode must be modified periodically. With the data gathering algorithm, the frequency of data gathering and energy consumption in intra-cluster could be reduced. The simulation results demonstrate that the data gathering algorithm is effective, and the system lifetime is prolonged.