Lossless Compression Algorithm Based on Hybrid Coding of Adaptive Huffman and Golomb-Rice for WSN
摘要
Aiming at the problem that traditional Wireless Sensor Network(WSN) data compression algorithms cannot take both compression efficiency and data loss into account,a fast and efficient Lossless Adaptive Compression(LAC) algorithm based on adaptive Huffman coding and Golomb-Rice coding is proposed.Hybrid coding of adaptive Huffman and Golomb-Rice is used to solve the problem of variable length and dynamic.Heuristic method is used to simply estimate non-negative Golomb-Rice coding parameters proposed.A rice mapping function is used to transform the Laplace distribution error term so as to approximate the geometric distribution of nonnegative integers,which are used as the input of entropy encoder.Adaptive entropy coding is used to independently compress sampling data block.Experimental results on real environment WSN dataset from SensorScope show that the proposed algorithm acnieves a compression ratio of 4.11 per sample,and can realize power savings of up to 70.61%.Besides,compression performance and compression rate of the proposed algorithm are better than that of S-LZW,LEC and other compression algorithms.