Abstract: With the ever-increasing data volume in enterprises,the needs of massive data storage capacity currently become a grand challenge in data centers,and researching shows that there are about 60% redundant data in storage systems．Therefore,the problems of high redundancy in data storage systems are paid much more attentions by resear-chers．Exploiting CPU resource to compare the data block’s fingerprint which is unique,data deduplication techniques can efficiently accomplish data reduction in storage systems,thus data deduplication techniques have become a hot topic in both industry and academia fields．Based on adequately analyzing and summarizing literatures on data deduplication techniques appeared in recent ten years,this paper first presented the principle of representative data deduplication systems,implementation mechanisms as well as evaluation methodologies after analyzing volume-level data deduplication system architecture．Second,we also focused on existing deduplication optimizing techniques with consideration of both the characteristics of data and scale of data deduplication systems．Finally four new research directions were given as follows by comparatively analyzing various application scenarios of data deduplication systems,including research of primary-Storage-Level data deduplication approaches,research of distributed data deduplication scheme for clustered storage systems,research of highly-efficient fingerprint searching techniques and research of intelligent data detection techniques.

Key words: Data deduplication,Deduplication ratio,System architecture,Metadata structure,I/O optimization