无线传感器网络中一种数据近似方法

无线传感器网络通常能量与通信带宽有限、计算与存储能力受限,这对数据的传输以及数据的分析与挖掘提出了新的挑战。本文提出了一种数据的近似方法,讨论了数据的压缩与近似恢复,并且在此基础上分析了数据的相似性度量。理论分析和实验结果表明,在保证数据精度的前提下,该方法能够有效地对数据进行压缩降维,节省存储空间和减少网络数据传输量;并且能够在压缩后的数据上进行数据的相似性度量,提高了数据聚类分析的效率。

A Data Approximation Method in Wireless Sensor Networks

Wireless sensor networks usually have limited energy and transmission bandwidth, and restricted computing and storage capacity, which pose new challenges in data dissemination and data analyzing and mining. This paper proposes a data approximation method, discusses data compression and approximate recovery, and analyzes its corresponding similarity measure. Theoretically and experimentally, under the circumstance of guaranteeing data precision, this method can compress data efficiently to save storage space, and reduce the amount of data transmission. Moreover, it can also analyze the similarity measure based on the compressed data, which can improve the efficiency of cluster analysis of data.