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COGNITIVE DEDUPLICATION-AWARE DATA PLACEMENT IN LARGE SCALE STORAGE SYSTEMS

机译:大规模重复数据删除系统中认知重复数据删除的位置

摘要

A method for a data placement that attempts to predict the most suitable placement, in terms of data reduction, of a newly created storage volume based on the volumes known attributes and the current placement of volumes to deduplication domains is disclosed. The system uses machine learning to perform improved deduplication-aware placement. The system attempts to predict the deduplication domain where a newly created volume would eventually have the best content sharing. The system does this by using the known attributes of the volume at the time of creation, such as owner, volume name, initial size, creation time, and the history of data already in the system and its placement.
机译:公开了一种用于数据放置的方法,该方法尝试基于卷的已知属性和卷到重复数据删除域的当前放置来预测新创建的存储卷的最合适放置(就数据缩减而言)。该系统使用机器学习来执行改进的重复数据删除感知放置。系统尝试预测重复数据删除域,其中新创建的卷最终将具有最佳的内容共享。系统通过使用创建时卷的已知属性(例如所有者,卷名,初始大小,创建时间以及系统中已有数据的历史及其放置)来执行此操作。

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