Multi-objective Based Performance Evaluation of Deduplication Approaches
Yujuan Tan, Zhichao Yan
Abstract
Yujuan Tan, Zhichao Yan
Abstract
Data deduplication is a lossless compression technology that has been widely used in storage systems for space optimization. However, due to the removal of redundant data, the data deduplication has negative influences on data writing, data reading and data reliability. In this paper, we propose a multi-objective based performance evaluation framework to analyze the data deduplication performances and evaluates existing well-known deduplication approaches with multiple performance objectives, including compression ratio, data read performance, data write performance, and data reliability.
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Data deduplication is a lossless compression technology that has been widely used in storage systems for space optimization. However, due to the removal of redundant data, the data deduplication has negative influences on data writing, data reading and data reliability. In this paper, we propose a multi-objective based performance evaluation framework to analyze the data deduplication performances and evaluates existing well-known deduplication approaches with multiple performance objectives, including compression ratio, data read performance, data write performance, and data reliability.
Key concepts: Data deduplication, Computer science, Lossless compression, Reliability (semiconductor), Data compression, Data mining, Database, Algorithm