传感器网络中一种基于一元线性回归模型的空时数据压缩算法
doi: 10.3724/SP.J.1146.2009.00704
A One-dimensional Linear Regression Model Based Spatial and Temporal Data Compression Algorithm for Wireless Sensor Networks
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摘要: 针对传感器网络中节点采样数据的空间和时间冗余特点以及节能要求，该文提出了一种基于一元线性回归模型的空时数据压缩算法ODLRST。ODLRST先在每个节点内进行消除时间冗余的数据压缩，再在节点汇集处对来自不同节点的数据消除空间冗余以进一步压缩数据。仿真实验证明，ODLRST能够极大地减少节点发送的数据量和网络中的通信流量，节省并平衡网络中的能量消耗。Abstract: Considering spatial and temporal redundancy of data and demand of saving energy in Wireless Sensor Networks (WSN), a One-Dimensional Linear Regression model based Spatial and Temporal(ODLRST) data compression algorithm, is proposed. By eliminating temporal redundancy of data in single node and spatial redundancy of data among nodes respectively in WSN, ODLRST greatly compresses these data. Simulation results show that ODLRST can reduce data size sent by nodes and network traffic in WSN, and save and balance energy consumption in the network.
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