FuzzyCAT:一种改进基于f变换的传感器数据压缩的新方法

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI:10.1145/2737095.2742921

Vasilisa Bashlovkina, Mohamed Abdelaal, Oliver E. Theel

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引用次数: 5

摘要

本文旨在开发一种新的压缩技术，打破压缩比与恢复精度之间的“螺旋式下降”。基于先前开发的模糊变换压缩(FTC)，我们设计并实现了该算法的改进版本，称为模糊压缩自适应变换(FuzzyCAT)。通过与LTC (Lightweight Temporal Compression)技术的比较研究表明，FuzzyCAT节点的传输成本远低于LTC (Lightweight Temporal Compression)技术，这使其成为无线传感器网络中数据压缩的理想选择。

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FuzzyCAT: a novel procedure for refining the F-transform based sensor data compression

This paper aims at developing a novel compression technique which breaks the "downward spiral" between compression ratio and recovery precision. Based on the previously developed Fuzzy Transform Compression (FTC), we design and implement a modified version of the algorithm, referred to as Fuzzy Compression Adaptive Transform (FuzzyCAT). The crux of FuzzyCAT is to adapt the transform parameters to the signal's curvature inferred from the time derivativesA comparative study with the Lightweight Temporal Compression (LTC) technique revealed that transmission costs of the FuzzyCAT nodes are much less than that of the LTC, which makes it an outstanding candidate for data compression in Wireless Sensor Networks.

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Proceedings of the 14th International Conference on Information Processing in Sensor Networks

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