Optimization of Lossless Compression Algorithms using Multithreading

S. P
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Abstract

The process of reducing the number of bits required to characterize data is referred to as compression. The advantages of compression include a reduction in the time taken to transfer data from one point to another, and a reduction in the cost required for the storage space and network bandwidth. There are two types of compression algorithms namely lossy compression algorithm and lossless compression algorithm. Lossy algorithms find utility in compressing audio and video signals whereas lossless algorithms are used in compressing text messages. The advent of the internet and its worldwide usage has not only raised the utility but also the storage of text, audio and video files. These multimedia files demand more storage space as compared to traditional files. This has given rise to the requirement for an efficient compression algorithm. There is a considerable improvement in the computing performance of the machines due to the advent of the multi-core processor. However, this multi-core architecture is not used by compression algorithms. This paper shows the implementation of lossless compression algorithms namely the Lempel-Ziv-Markov Algorithm, BZip2 and ZLIB algorithms using the concept of multithreading. The results obtained prove that the ZLIB algorithm proves to be more efficient in terms of the time taken to compress and decompress the text. The comparison is done for both compressions without multithreading and compression with multi-threading.
基于多线程的无损压缩算法优化
减少表征数据所需的比特数的过程称为压缩。压缩的优点包括减少将数据从一个点传输到另一个点所花费的时间,以及减少存储空间和网络带宽所需的成本。压缩算法有两种类型,即有损压缩算法和无损压缩算法。有损算法用于压缩音频和视频信号,而无损算法用于压缩文本消息。互联网的出现及其在全球范围内的使用不仅提高了实用性,而且提高了文本、音频和视频文件的存储。与传统文件相比,这些多媒体文件需要更多的存储空间。这就提出了对高效压缩算法的要求。由于多核处理器的出现,机器的计算性能有了相当大的提高。然而,压缩算法不使用这种多核架构。本文介绍了利用多线程的概念实现无损压缩算法,即Lempel-Ziv-Markov算法、BZip2和ZLIB算法。得到的结果证明,ZLIB算法在压缩和解压缩文本所需的时间方面更有效。对不使用多线程的压缩和使用多线程的压缩进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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