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Cloud object storage based Continuous Data Protection(cCDP)

机译:基于云对象存储的持续数据保护(cCDP)

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Continuous Data Protection (CDP) enables recoverability to any point in time (time travel) facilitated via journaling of every write made by a system to disk. Stringent storage performance and capacity requirements for journaling make CDP a very high cost solution leading to limited adoption. In this work we first explore the feasibility of building such a CDP function on top of cheap commodity storage exposed via cloud object stores. Based on this analysis, we propose cCDP - a Cloud Continuous Data Protection framework that efficiently combines cloud object stores with edge caching to address requirements of low cost, high capacity, low latency and high storage throughput. cCDP with careful tuning can not only meet but surpasses the write throughput and latency requirements of CDP with minimal buffer overheads (<; 1%). Recovery lookup performance (Identification & Ordering) of cCDP with hybrid data layout is within 28% of Btree based temporal data layout and is about 52.7% better than the naive data layout with name encoding with significantly lower edge buffer and write throughput overheads than the Btree based temporal data layout.
机译:连续数据保护(CDP)可以通过系统到磁盘所做的每次写入的日志促进的任何时间点(时间旅行)的可恢复性。严格的存储性能和日记的容量要求使CDP成为一个非常高的成本解决方案,导致采用有限。在这项工作中,我们首先探讨在通过云对象商店公开的廉价商品存储顶部建立这种CDP功能的可行性。在此分析的基础上,我们提出了CCDP - 云连续数据保护框架,有效地将云对象存储与边缘缓存结合到地址低成本,高容量,低延迟和高存储吞吐量的要求。 CCDP具有谨慎调整,不仅可以满足但超越CDP的写入吞吐量和延迟要求,具有最小缓冲架开销(<; 1%)。 CCDP的CCDP具有混合数据布局的恢复查找性能(识别和订购)在BTREE的时间数据布局的28%范围内,比NAIVE数据布局更好地具有与较低的边沿缓冲器的名称和写入吞吐量开销的NAIVE数据布局比BTREE更好基于时间数据布局。

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