Data Compression Algorithm Research Based On Piecewise Representation For Wireless Sensor Networks

Wireless Sensor Network is a self-organized network that consists of a large of sensor nodes with a specific function by means of wireless communication. Generally, the sensor nodes are deployed in complex terrain conditions, and they are powered by batteries, which determines that each node has only a certain life cycle. The communication has consumes most of the energy of the network in the Wireless Sensor Network(WSN).For using data compression can reduce the redundancy of the network, therefore data compression can be used to save energy effectively, thereby extending the lifetime of the sensor nodes.Piecewise representation is a lossy compression algorithm, which is simple and has low complexity, suitable for wireless sensor networks. This paper proposed several piecewise representation algorithms based on time correlation of sensor data. The major work is as follows:First of all, aiming at Time-dependent characteristics between source data detected in wireless sensor networks (WSN), a data compressing algorithm based on area vector (AVA) and the derivation of the area threshold are proposed. The authors set area threshold as the standard and use the superposition of area vector to improve the accuracy and efficiency. Experimental results show this algorithm can indicate better compression ratio, performance and reduce the energy consumption of sensor nodes.Secondly, some deficiencies exist for AVA algorithm, an improved idea of maximizing the line piecewise. The specific ways is to extend the segment at the end of each of AVA algorithm. In addition, there is a flaw that the compression ratio of AVA algorithm may be negative when the threshold is a small value. This paper designed a new data compressing algorithm-the improve AVA algorithm, which combines with the Huffman algorithm. Experimental results show that this algorithm can indicate better compression ratio and performance.