Jiu shan ma zai fen bu shi cun chu xi tong zhong de zui you xiu fu fang fa yi ji tong yi guan li de yan jiu

Ph.D.Modern data centers provide storage services by running distributed storage systems on many storage servers, where failures become common cases. To ensure data availability and durability, distributed storage systems either apply replication, where each block is stored with multiple replicas, or erasure coding, where a number of data blocks are encoded as a set of coded-blocks, such that an unavailable data block can be reconstructed by a subset of coded-blocks. Compared with replication, erasure coding provides data availability with lower storage overhead; thus, many distributed storage systems apply erasure coding to provide reliable storage services. However, erasure coding has two drawbacks. Firstly, erasure coding incurs high repair penalty when reconstructing an unavailable data block, which requires much more than the size of the original data block to be transferred across the network, and thus leads to poor repair performance. Secondly, it requires non-trivial engineering work to introduce new erasure coding solutions to existing distributed storage systems as erasure coding management is tightly coupled with the basic workflows of distributed storage systems. In this thesis, we focus on solving these two problems and enable optimal repair and unified management of erasure coding in distributed storage systems.We first focus on improving the repair performance in a hierarchical data center, which is often bottlenecked by cross-rack network transfer. Recent theoretical results show that the cross-rack repair traffic can be minimized through repair layering, whose idea is to partition a repair operation into inner-rack and cross-rack layers. However, how repair layering should be implemented and deployed in practice remains an open issue. We address this issue by proposing a practical repair layering framework called DoubleR. We design two families of practical double regenerating codes (DRC), which not only minimize the cross-rack repair traffic but also have several practical properties that improve state-of- the-art regenerating codes. We implement and deploy DoubleR atop HDFS-RAID (Facebook’s version of Hadoop Distributed File System) and show that DoubleR maintains the theoretical guarantees of DRC and improves the repair performance of regenerating codes in both node recovery and degraded read operations.We then focus on improving the repair performance in general erasure-coded storage by presenting a technique, repair pipelining. By pipelining the repair of failed data in small-size units across storage nodes, repair pipelining reduces the single-block repair time to approximately the same as the normal read time for a single block in homogeneous environments. We further design different variants of repair pipelining algorithms for heterogeneous environments and multi-block repair operations. We implement a repair pipelining prototype, called ECPipe, and integrate it as a middleware system into three open-source distributed storage systems, including HDFS-RAID, Hadoop-3.1.1 HDFS, and Quantcast File System. Experiments on a local testbed and Amazon EC2 show that repair pipelining significantly improves the performance of degraded reads and full-node recovery over existing repair techniques.Finally, we focus on solving the problem of managing different erasure coding solutions in distributed storage systems. Research studies have proposed theoretically proven erasure codes or efficient repair algorithms to make erasure coding more viable. However, integrating new erasure coding solutions into existing distributed storage systems is a challenging task and requires nontrivial re-engineering of the underlying storage workflows. We present OpenEC, a unified and configurable framework for readily deploying a variety of erasure coding solutions into existing distributed storage systems. OpenEC decouples erasure coding management from the storage workflows of distributed storage systems, and provides erasure coding designers with configurable controls of erasure coding operations through a directed-acyclic-graph- based programming abstraction. We prototype OpenEC on HDFS-RAID and Hadoop-3.0 HDFS with limited code modifications. Experiments on a local cluster and Amazon EC2 show that OpenEC preserves both the operational performance and the properties of erasure coding solutions; OpenEC can also automatically optimize erasure coding operations to improve repair performance.現代數據中心通過分布式存儲系統向外提供存儲服務。大型的數據中心由很多存儲服務器組成, 在這種情況下，服務器發生故障導致數據丟失或者受損成為了一個很常見的問題。为了保證數據可用性和持久性，分布式存儲系統可以應用多副本技術（每個數據塊存儲多個副本），或者糾刪碼技術（一定數量的數據塊經過編碼，使得其中受損的數據塊可以由一部分未受損的數據塊修復）。與多副本技術相比，糾刪碼技術能在提供數據可用性的同時降低存儲開銷，所以許多分布式存儲系統應用糾刪碼來確保數據的可靠性。然而，糾刪碼技術有兩個缺點。第一，用糾刪碼來修復數據的時候需要從網絡上下載大量的數據（比需要修復的數據量大得多），這導致了數據修復的性能不好。第二，由於糾刪碼的管理與分布式存儲系統中的基本操作緊耦合，導致將新的糾刪碼解決方案應用到現有的分布式存儲中需要大量工程才能做到。本論文主要研究並解決了這兩個問題，使得糾刪碼能為分布式存儲系統提供最優的修復性能，同時，也為糾刪碼的管理提供了統一的框架，使得糾刪碼能很快的應用到分布式存儲系統中。首先，我們提高了分層網絡數據中心中糾刪碼的數據修復性能。在分層網絡數據中心中，跨機架網絡傳輸性能是整個糾刪碼數據修復過程的瓶頸。理論研究結果已經證明分層數據修復技術能最小化糾刪碼在數據修復過程中產生的跨機架傳輸的數據量。它將數據修復操作分成兩層，即機架內的部分修復與跨機架的數據整合。然而，怎樣將分層數據修復技術應用到分布式存儲系統中依然是一個開放性的研究問題。我們提出了一個分層數據修復的框架，DoubleR，來解決這個問題。我們首先設計了兩組重複再生碼（DRC），它們不僅能最小化數據修復過程中產生的跨機架傳輸的數據量，而且，它們能提升經典再生碼的數據修復性能。然後，我們在HDFS-RAID 中實現了分層數據修復框架DoubleR，並將我們設計的兩組重複再生碼通過DoubleR 應用到了HDFS 中。我們的實驗表明DRC 能提升再生碼的數據修復性能。第二，我們提出了流水線數據修復的技術，repair pipelining,來提升一般網絡結構的數據中心中糾刪碼的數據修復性能。這個技術將一個數據塊的修復分為了很多個小數據片的修復，並流水線的修復所有的數據片。在扁平化網絡架構的數據中心中，流水線數據修復能降低單個數據塊的修復時間，使得其接近正常讀一個數據塊的時間。同時我們也擴展了repair pipelining 使它能夠支持分層網絡架構數據中心，以及同一條帶中多數據塊的同時修復。我們設計並實現了應用repair pipelining 進行數據修復的中間件，ECPipe，並將repair pipelining 應用到了三個開源的分布式存儲系統中（HDFS-RAID, Hadoop-3.1.1 HDFS, Quantcast File System）。我們的實驗證明repair pipelining 極大的提升了分布式存儲系統的數據修復性能。第三，我們解決了在分布式存儲系統中管理多種糾刪碼解決方案的問題。為了提升糾刪碼在分布式存儲系統中的可用性，研究人員既從理論上設計了新的，更實用的糾刪碼，也提出了更有效的數據修復算法。然而，將這些新的糾刪碼解決方案應用到現有的分布式存儲系統中是一個非常具有挑戰性的工作。這需要大量的修改分布式存儲系統的工作流程。為了解決這個問題，我們為分布式存儲系統設計了一個統一的，可編程控制的糾刪碼管理系統，OpenEC。它可以很快的將一個糾刪碼解決方案應用到現有的分布式存儲系統中。OpenEC 將糾刪碼的控制模塊從分布式存儲系統的存儲流程中解構出來，並通過提供一種基於有向圖的編程模型讓糾刪碼設計人員能在這個系統中方便的控制糾刪碼的各種操作。在修改少量系統源代碼的情況下，我們將OpenEC 應用到了HDFS-RAID 和Hadoop 3.0 HDFS 中。我們的實驗結果表明，OpenEC 不僅能保證糾刪碼各種操作的性能，還能保持不同糾刪碼設計的特性，同時OpenEC 還可以自動優化糾刪碼的操作來提升它在分布式存儲系統中的性能。Li, Xiaolu.Thesis Ph.D. Chinese University of Hong Kong 2020.Includes bibliographical references (leaves 161-175).Abstracts also in Chinese.Title from PDF title page (viewed on 20, September 2021).Li, Xiaolu