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Due to its better scalability, Key-Value (KV) store has superseded traditional relational databases for many applications, such as data deduplication, on-line multi-player gaming, and Internet services like Amazon and Facebook. The KV store efficiently supports two operations (key lookup and KV pair insertion) through an index structure that maps keys to their associated values. The KV store is also...
The complexity of distributed storage systems makes it difficult to evaluate fundamentally new data placement policies for energy efficiency in real-world systems. Simulation studies allow us to quickly prototype and test energy-efficient management policies. Unfortunately, there is a lack of tools in the public domain that support such studies. We introduce EEffSim, a highly configurable energy simulator...
Data deduplication has recently become commonplace in most secondary storage and even in some primary storage for the capacity optimization purpose. Aside from its write performance, read performance of the deduplication storage has been gaining in significance with a wide range of its deployments. In this paper, we emphasize the importance of read performance in reconstituting a data stream from...
Reliability in deduplication storage has not attracted much research attention yet. To provide a demanded reliability for an incoming data stream, most deduplication storage systems first carry out deduplication process by eliminating duplicates from the data stream and then apply erasure coding for the remaining (unique) chunks. A unique chunk may be shared (i.e., duplicated) at many places of the...
A Bloom Filter (BF) is a data structure based on probability to compactly represent/record a set of elements (keys). It has wide applications on efficiently identifying a key that has been seen before with minimum amount of recording space used. BF is heavily used in chunking based data de-duplication. Traditionally, a BF is implemented as in-RAM data structure; hence its size is limited by the available...
A predominant portion of Internet services, like content delivery networks, news broadcasting, blogs sharing and social networks, etc., is data centric. A significant amount of new data is generated by these services each day. To efficiently store and maintain backups for such data is a challenging task for current data storage systems. Chunking based deduplication (dedup) methods are widely used...
There is a huge amount of duplicated or redundant data in current storage systems. So data de-duplication, which uses lossless data compression schemes to minimize the duplicated data at the inter-file level, has been receiving broad attention in recent years. But there are still research challenges in current approaches and storage systems, such as: how to chunking the files more efficiently and...
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