云存储中数据压缩技术的研究

发布时间：2018-04-14 10:18

本文选题：云存储 + 数据压缩　；参考：《云南大学》2013年硕士论文

【摘要】：近些年,云存储的出现对传统存储领域产生了深刻影响,是目前企业界和学术界共同关注的热点。但是目前学术界对存储的研究大都关注于带宽、安全及基础设施方面,很少放在云存储这个大环境下来考虑,尤其是对在云存储环境中面临海量数据时数据压缩技术对负载均衡的影响。另外,在对数据压缩技术进行研究时,往往通过牺牲空间来换取低时间复杂度,造成了数据在解压缩时有损。因此无法保障数据压缩前后的一致性。最后,对私有云存储系统的研究,存在着众多的开源版本,如何选取适合私有的、灵活的及可定制的云存储解决方案是我们面临的又一重大问题。针对上述问题,本文将对数据压缩技术进行分析和研究,尤其是以字典编码及其延伸出来的LZZ77算法、LZ78算法及LZW算法作为研究对象,分析了各自的优缺点,在此基础上本文提出了一种改进型LZW算法,它在负载均衡,系统扩展方面有着天然的优势。改进型LZW算法在提高算法效率和保护用户服务质量的前提下,可以将数据冗余压缩到最小,以保证尽可能少的无用信息。最后,本文在此基础上,实现了一种私有云存储平台。论文的主要内容和工作包括以下几个方面： ·分析了云存储及其数据压缩技术在国内外研究现状,结合目前存在的问题,我们得出了把数据压缩技术作为研究重点的合理性和必要性。 ·针对数据压缩技术领域研究状况,我们提出了一种改进型LZW算法且详细分析了其性能。通过实验验证了该算法在数据压缩比、压缩时间及压缩效果方面的优越性,为以后在该领域的研究提供借鉴价值。 ·基于上述研究,本文针对搭建私有云存储的特点,我们实现了一个私有云存储系统MongoDB,给想要搭建私有云存储环境的用户和科研团体打下了基础。
[Abstract]:In recent years, the emergence of cloud storage has a profound impact on the traditional storage field.However, at present, most of the research on storage in academic circles is focused on bandwidth, security and infrastructure, and is rarely considered in the general environment of cloud storage.Especially, the influence of data compression technology on load balancing in cloud storage environment is discussed.In addition, in the research of data compression technology, we often sacrifice space for low time complexity, which results in the loss of data decompression.Therefore, the consistency of data compression can not be guaranteed.Finally, there are many open source versions in the research of private cloud storage system. How to select suitable private, flexible and customizable cloud storage solutions is another important problem we face.In view of the above problems, this paper will analyze and study the data compression technology, especially take the dictionary coding and its extended LZZ77 algorithm, LZ78 algorithm and LZW algorithm as the research objects, and analyze their advantages and disadvantages.On this basis, an improved LZW algorithm is proposed, which has natural advantages in load balancing and system expansion.The improved LZW algorithm can reduce the data redundancy to the minimum while improving the efficiency of the algorithm and protecting the user's quality of service so as to ensure as little useless information as possible.Finally, this paper implements a private cloud storage platform.The main contents and work of the thesis include the following aspects:This paper analyzes the current research situation of cloud storage and its data compression technology at home and abroad. Combined with the existing problems, we get the rationality and necessity of taking data compression technology as the research focus.In view of the research status in the field of data compression, we propose an improved LZW algorithm and analyze its performance in detail.The superiority of the algorithm in data compression ratio, compression time and compression effect is verified by experiments, which provides reference value for future research in this field.Based on the above research, we implement a private cloud storage system, MongoDB-based, aiming at the characteristics of building private cloud storage, which lays the foundation for users and research groups who want to build private cloud storage environment.
【学位授予单位】：云南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP333

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