An Adaptive Compression Algorithm for Energy-Efficient Wireless Sensor Networks

Energy efficiency is one of the most important design metrics for wireless sensor networks. As sensor data always have redundancies, compression is introduces for energy savings. However, different emphases on algorithm design influence the operation effect of compression under various applications and network environments. In order to improve the energy utilization efficiency for the whole network, an adaptive data compression is proposed in this paper, which realizes a real-time adjustment of compression strategy. By prediction and feature extraction of several relevant parameters, the algorithm provides optimal execution strategies for each sensor node in the network. The simulation results show that, the proposed compression scheme enables all nodes to complete data communication with near optimal energy consumptions, and the maximum deviation against the ideal condition is no more than 5%. Moreover, the algorithm can effectively act on different data precision, transmit power and retransmission rate to meet the dynamic requirements of the network with only a few costs introduced.