Research On Energy-Efficient Data Compression Scheme In Wireless Sensor Networks

:Energy is the most important but limited resources for wireless sensor networks, and the most of energy is consumed by the wireless communications. How to use the limited energy efficiently is a key issue facing wireless sensor networks. Data compression can effectively reduce the amount of data communication based on the temporal and spatial correlation of monitoring data, which is an important energy-saving method for sensor nodes. However, data compression increased the processing energy consumption in microcontroller unit through the communication energy is reduced. Therefore, how to greatly increase the energy gain though data compression is the key solution to reduce the energy consumption of the node in wireless sensor network.The research on energy-efficient compression mainly involves two aspects:the evaluation method and the energy-efficiency improvement scheme. Therefore, this thesis mainly studied on three questions:the energy-efficiency evaluation scheme of data compression for the general hardware platform, the source-level energy optimization method for data compression, transmitting power-sensing data compression scheme.Firstly, in order to objectively and effectively evaluate the energy saving effect can be achieved of data compression, an improved evaluation scheme has been proposed on the basis of the evaluation criterion have been given, which separated the hardware and algorithms factor. Secondly, in order to improve the execution efficiency of the data compression algorithm and reduces energy consumption of algorithm execution, the source-level optimization and energy-saving method for compression algorithm has been proposed. Thirdly, in order to maintain the energy income of data compression when the transmission power is changed, an algorithm adjustment scheme has been presented which is well suit for the changeable transmission power of node.This dissertation improved the data compression energy-efficiency though the method studying and scheme designing concern on the energy-efficiency evaluation, source-level energy optimization and algorithm adjustment scheme. The feasibility and effectiveness of the method and scheme have been verified though some test base on the typical hardware environment. The theoretical analysis and experimental results have shown that the proposed method and scheme can effectively improve the overall energy efficiency of the wireless sensor nodes.