无线传感器网络基于时空差分阈值Huffman数据压缩

Wireless sensor network based on a spatio-temporal differential threshold Huffman data compression

摘要:

针对无线传感网络（WSN）中节点采集数据后传输消耗能量的问题进行研究，该文提出了一种基于时空差分阈值Huffman模型对时空的数据进行压缩的算法。该算法通过节点在当前时刻采集的数据与节点的上一个时刻的数据进行差值，同时对同一簇内空间的节点差分后数据进行对比分析和减少空间的数据量，再对差值进行动态的Huffman编码。与传统WSNs的数据压缩算法相比，数据的压缩比提高到了30%，网络的生命周期提升了80%和降低了节点的死亡率，同时也保证了节点数据采集的准确性。

Abstract:

In view of the energy consumption of data transmission in wireless sensor network (WSN), a temporal and spatial different way threshold Huffman model is proposed to compress spatio-temporal data in the article. The algorithm makes a difference between the data collected at this time and the data stored in the node and has relative differences in the data of the nodes in a certain space, then encoding dynamically-Huffman of the difference. Compared with the traditional WSNs data compression algorithm, the way make the compression ratio of the data mentioned 30%, while the life cycle of the network is increased by 80% and the death rate of the nodes is also reduced, and the accuracy of the data acquisition is ensured.