Data Aggregation Mechanism based on Wavelet-entropy for Wireless Sensor Networks

Wireless sensor networks consist of a large number of sensor nodes with limited battery power, and how to use energy of sensor nodes more efficiently to extend the lifetime of networks is a primary goal in the design of wireless sensor networks. Data aggregation can reduce the traffic in network by utilizing the abilities of local computation and storage of sensor nodes. In this paper, we propose a novel data aggregation scheme based on wavelet-entropy (DAME in short) for wireless sensor networks. Firstly, we use multi-scale wavelet transforms to spread signals in multi-scale range, and then aggregate information using wavelet-entropy discriminance theorem in cluster members and cluster heads with LEACH clustering algorithm to reduce transmitting packets. Finally, we evaluate the performance of proposed data aggregation based on wavelet-entropy scheme by simulations.