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RSEDP: an effective hybrid data placement algorithm for large-scale storage systems

机译:RSEDP:一种用于大型存储系统的有效混合数据放置算法

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The reliability and scalability of large-scale network storage systems are confronted with big challenges, which require designing a reliable, scalable, and efficient data placement algorithm. Previous techniques can only partially satisfy these requirements. In this work, we develop an effective hybrid approach, RSEDP, which combines reliable replication data placement (RRDP) with scalable and efficient data placement (SEDP) to achieve the requirements mentioned above. RRDP distributes replicated data over large-scale heterogeneous network storage systems in which the same replica is distributed to different devices and not inclined to consecutive devices, achieving high redundancy degree and failure resilience. SEDP assigns data evenly among devices according to their weight and scales well to the expansions or curtailments of the systems. In order to take the advantages of both RRDP and SEDP, RSEDP integrates them by categorizing data into hot and cold data based on their access frequency, placing hot data by RRDP, and distributing the remainder by SEDP. The theoretical analysis and the experimental study show that the combined RSEDP can increase redundancy degree and failure resilience, and has a good scalability and time efficiency with small memory overhead.
机译:大型网络存储系统的可靠性和可扩展性面临着巨大的挑战,这要求设计一种可靠,可扩展且高效的数据放置算法。先前的技术只能部分满足这些要求。在这项工作中,我们开发了一种有效的混合方法RSEDP,该方法将可靠的复制数据放置(RRDP)与可伸缩且有效的数据放置(SEDP)相结合,从而达到上述要求。 RRDP在大型异构网络存储系统上分发复制的数据,在大型异构网络存储系统中,相同的副本分发到不同的设备,并且不倾向于连续的设备,从而实现了高冗余度和故障恢复能力。 SEDP根据设备的重量在设备之间平均分配数据,并且可以根据系统的扩展或缩减来很好地扩展。为了利用RRDP和SEDP的优势,RSEDP通过将数据根据它们的访问频率分类为热数据和冷数据,通过RRDP放置热数据,然后通过SEDP分配其余数据来将它们集成。理论分析和实验研究表明,组合的RSEDP可以提高冗余度和故障恢复能力,并具有良好的可扩展性和时间效率,而内存开销却很小。

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