By Daehee Kim, Sejun Song, Baek-Young Choi
This publication introduces basics and trade-offs of knowledge de-duplication innovations. It describes novel rising de-duplication strategies that get rid of replica facts either in garage and community in a good and powerful demeanour. It explains locations the place reproduction facts are originated, and offers suggestions that get rid of the reproduction information. It classifies latest de-duplication suggestions reckoning on dimension of unit information to be in comparison, where of de-duplication, and the time of de-duplication. bankruptcy three considers redundancies in e-mail servers and a de-duplication strategy to bring up relief functionality with low overhead via switching chunk-based de-duplication and file-based de-duplication. bankruptcy four develops a de-duplication process utilized for cloud-storage provider the place unit information to be in comparison should not physical-format yet logical structured-format, decreasing processing time successfully. bankruptcy five monitors a community de-duplication the place redundant facts packets despatched by way of consumers are encoded (shrunk to small-sized payload) and decoded (restored to unique measurement payload) in routers or switches that allows you to distant servers via community. bankruptcy 6 introduces a cellular de-duplication method with snapshot (JPEG) or video (MPEG) contemplating functionality and overhead of encryption set of rules for defense on cellular device.
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Extra info for Data Deduplication for Data Optimization for Storage and Network Systems
3 Existing Solutions File-level deduplication is used for Microsoft Exchange 2003 and 2007 based on a SIS . SIS stores ﬁle contents to a ‘SIS Common Store’. In SIS, a user ﬁle is managed by a SIS link that is a reference to a ﬁle called the ‘Common Store File’. Whenever SIS detects duplicate ﬁles, SIS links are created automatically and ﬁle contents are saved to the common store. SIS consists of a ﬁle system ﬁlter library that implements links and a user-level service detecting duplicate ﬁles that are replaced by links.
Thus, the dedupBlock() function ﬁrst checks whether there is a duplicate ﬁle with an index of the current ﬁle. If a ﬁle is redundant, the ﬁle is not separated into blocks. An index of the ﬁle is saved to the index table using the saveInCache() function, and the dedupBlock() function ends. If the current ﬁle is not a duplicate, there could be similar ﬁles with the same blocks. setAvgChunkSize(blkSize). The chunkWrapper object maintains all environment variables related to chunking. We go into detail on the chunkWrapper class in the next section.
Meanwhile, if a system removes redundancies directly in a write path within a conﬁned storage space, it is better to eliminate redundant data before storage. On the other hand, if a system has residual (or idle) time or enough space to store data temporarily, deduplication can be performed after the data are placed in temporary storage. In this chapter, we classify existing deduplication techniques based on granularity, place of deduplication and deduplication time. We start by explaining how to efﬁciently detect redundancy using chunk index caches and bloom ﬁlters.