The huge blast of information caused a lot of dilemmas in both storage and retrieval procedures. The enlargement in a massive quantity of digital data requirements imposes more storage space, which in turn radically increases performance and cost of backup. Data deduplication is one of the techniques that vanishes replicated data, decreases the bandwidth, and minimizes the disk usage and cost. Since various researches have been broadly considered in the literature, this paper reviews the ideas, categories, and different storage approaches that use data deduplication. Apart from the well-known classification that uses Granularity, Side, Timing, and Implementation for classifying the deduplication approaches, a new classification principle is adopted using the storage location. This classification identifies and describes the diverse methods. Moreover, the deduplication systems are comprehensively described according to the storage location, including Local, Centralized, and Clustered storage systems. Furthermore, the describing objectives, used techniques, features, and drawbacks of the most advanced methods of each type are broadly tackled. Finally, the major deduplication systems' challenges are recognized and illustrated.

中文翻译：

---

重复数据删除存储系统新分类调查

巨大的信息爆炸在存储和检索过程中造成了很多困境。海量数字数据需求的扩大带来了更多的存储空间，从而从根本上提高了备份的性能和成本。重复数据删除是消除复制数据、减少带宽以及最小化磁盘使用和成本的技术之一。由于文献中广泛考虑了各种研究，本文回顾了使用重复数据删除的思想、类别和不同的存储方法。除了使用Granularity、Side、Timing和Implementation对重复数据删除方法进行分类的众所周知的分类之外，还采用了使用存储位置的新分类原则。这种分类识别并描述了不同的方法。此外，重复数据删除系统根据存储位置进行了全面的描述，包括本地、集中和集群存储系统。此外，广泛解决了每种类型最先进方法的描述目标、使用的技术、特征和缺点。最后，认识到并说明了主要的重复数据删除系统面临的挑战。