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首页> 外文期刊>Journal of Sensors >Fast Algorithm of Truncated Burrows-Wheeler Transform Coding for Data Compression of Sensors
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Fast Algorithm of Truncated Burrows-Wheeler Transform Coding for Data Compression of Sensors

机译：截断的Burrows-Wheeler变换编码的传感器数据压缩快速算法

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摘要

Lots of sensors in the IoT (Internet of things) may generate massive data, which will challenge the limited sensor storage and network bandwidth. So the study of big data compression is very useful in the field of sensors. In practice, BWT (Burrows-Wheeler transform) can gain good compression results for some kinds of data, but the traditional BWT algorithms are neither concise nor fast enough for the hardware of sensors, which will limit the BWT block size in a very small and incompetent scale. To solve this problem, this paper presents a fast algorithm of truncated BWT named “CZ-BWT algorithm” and implements it in the shareware named “ComZip.” CZ-BWT supports the BWT block up to 2 GB (or larger) and uses the bucket sort. It is very fast with the time complexity O(N) and fits the big data compression. The experiment results indicate that ComZip with the CZ-BWT filter is obviously faster than bzip2, and it can obtain better compression ratio than bzip2 and p7zip in some conditions. In addition, CZ-BWT is more concise than current BWT with SA (suffix array) sorts and fits the hardware BWT implementation of sensors.
机译：物联网中的许多传感器可能会生成大量数据，这将挑战有限的传感器存储和网络带宽。因此，大数据压缩的研究在传感器领域非常有用。实际上，BWT（Burrows-Wheeler变换）可以对某些类型的数据获得良好的压缩结果，但是传统的BWT算法对于传感器的硬件既不简洁也不足够快，这将BWT块的大小限制在很小的范围内。不称职的规模。为了解决这个问题，本文提出了一种名为“ CZ-BWT algorithm”的截断BWT快速算法，并在名为“ ComZip”的共享软件中实现。 CZ-BWT支持最大2 GB（或更大）的BWT块，并使用存储桶排序。时间复杂度为O（N）时非常快，适合大数据压缩。实验结果表明，带有CZ-BWT过滤器的ComZip明显比bzip2快，并且在某些条件下它可以获得比bzip2和p7zip更好的压缩率。此外，CZ-BWT比当前带有SA（后缀数组）的BWT更加简洁，并且适合传感器的硬件BWT实现。

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