Unequaled improvements in processor and I/O speeds make many applications such as databases and operating systems to be increasingly I/O bound. Many schemes such as disk caching and disk mirroring have been proposed to address the problem. In this thesis we focus only on disk mirroring. In disk mirroring, a logical disk image is maintained on two physical disks allowing a single disk failure to be transparent to application programs. Although disk mirroring improves data availability and reliability, it has two major drawbacks. First, writes are expensive because both disks must be updated. Second, load balancing during failure mode operation is poor because all requests are serviced by the surviving disk. Distorted mirrors was proposed to address the write problem and interleaved declustering to address the load balancing problem. In this thesis we perform a comparative study of these two schemes under various operating modes. In addition we also study traditional mirroring to provide a common basis for comparison.

雲存儲是一個新興的服務模式，讓個人和企業的數據備份外包予較低成本的遠程雲服務提供商。本論文提出的方法，以確保數據的安全性和雲備份系統的可靠性。 / 在本論文的第一部分，我們提出 FadeVersion，安全的雲備份作為今天的雲存儲服務上的安全層服務的系統。 FadeVersion實現標準的版本控制備份設計，從而消除跨不同版本備份的冗餘數據存儲。此外，FadeVersion在此設計上加入了加密技術以保護備份。具體來說，它實現細粒度安全删除，那就是，雲客戶可以穩妥地在雲上删除特定的備份版本或文件，使有關文件永久無法被解讀，而其它共用被删除數據的備份版本或文件將不受影響。我們實現了試驗性原型的 FadeVersion並在亞馬遜S3之上進行實證評價。我們證明了，相對於不支援度安全删除技術傳統的雲備份服務 FadeVersion只增加小量額外開鎖。 / 在本論文的第二部分，提出 CFTDedup一個分佈式代理系統，利用通過重複數據删除增加雲存儲的效率，而同時確保代理之間的崩潰容錯。代理之間會進行同步以保持重複數據删除元數據的一致性。另外，它也分批更新元數據減輕同步帶來的開銷。我們實現了初步的原型CFTDedup並通過試驗台試驗，以存儲虛擬機映像評估其重複數據删除的運行性能。我們還討論了幾個開放問題，例如如何提供可靠、高性能的重複數據删除的存儲。我們的CFTDedup原型提供了一個平台來探討這些問題。 / Cloud storage is an emerging service model that enables individuals and enterprises to outsource the storage of data backups to remote cloud providers at a low cost. This thesis presents methods to ensure the data security and reliability of cloud backup systems. / In the first part of this thesis, we present FadeVersion, a secure cloud backup system that serves as a security layer on top of todays cloud storage services. FadeVersion follows the standard version-controlled backup design, which eliminates the storage of redundant data across different versions of backups. On top of this, FadeVersion applies cryptographic protection to data backups. Specifically, it enables ne-grained assured deletion, that is, cloud clients can assuredly delete particular backup versions or files on the cloud and make them permanently in accessible to anyone, while other versions that share the common data of the deleted versions or les will remain unaffected. We implement a proof-of-concept prototype of FadeVersion and conduct empirical evaluation atop Amazon S3. We show that FadeVersion only adds minimal performance overhead over a traditional cloud backup service that does not support assured deletion. / In the second part of this thesis, we present CFTDedup, a distributed proxy system designed for providing storage efficiency via deduplication in cloud storage, while ensuring crash fault tolerance among proxies. It synchronizes deduplication metadata among proxies to provide strong consistency. It also batches metadata updates to mitigate synchronization overhead. We implement a preliminary prototype of CFTDedup and evaluate via test bed experiments its runtime performance in deduplication storage for virtual machine images. We also discuss several open issues on how to provide reliable, high-performance deduplication storage. Our CFTDedup prototype provides a platform to explore such issues. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Rahumed, Arthur. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 47-51). / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Cloud Based Backup and Assured Deletion --- p.1 / Chapter 1.2 --- Crash Fault Tolerance for Backup Systems with Deduplication --- p.4 / Chapter 1.3 --- Outline of Thesis --- p.6 / Chapter 2 --- Background and Related Work --- p.7 / Chapter 2.1 --- Deduplication --- p.7 / Chapter 2.2 --- Assured Deletion --- p.7 / Chapter 2.3 --- Policy Based Assured Deletion --- p.8 / Chapter 2.4 --- Convergent Encryption --- p.9 / Chapter 2.5 --- Cloud Based Backup Systems --- p.10 / Chapter 2.6 --- Fault Tolerant Deduplication Systems --- p.10 / Chapter 3 --- Design of FadeVersion --- p.12 / Chapter 3.1 --- Threat Model and Assumptions for Fade Version --- p.12 / Chapter 3.2 --- Motivation --- p.13 / Chapter 3.3 --- Main Idea --- p.14 / Chapter 3.4 --- Version Control --- p.14 / Chapter 3.5 --- Assured Deletion --- p.16 / Chapter 3.6 --- Assured Deletion for Multiple Policies --- p.18 / Chapter 3.7 --- Key Management --- p.19 / Chapter 4 --- Implementation of FadeVersion --- p.20 / Chapter 4.1 --- System Entities --- p.20 / Chapter 4.2 --- Metadata Format in FadeVersion --- p.22 / Chapter 5 --- Evaluation of FadeVersion --- p.24 / Chapter 5.1 --- Setup --- p.24 / Chapter 5.2 --- Backup/Restore Time --- p.26 / Chapter 5.3 --- Storage Space --- p.28 / Chapter 5.4 --- Monetary Cost --- p.29 / Chapter 5.5 --- Conclusions --- p.30 / Chapter 6 --- CFTDedup Design --- p.31 / Chapter 6.1 --- Failure Model --- p.31 / Chapter 6.2 --- System Overview --- p.32 / Chapter 6.3 --- Distributed Deduplication --- p.33 / Chapter 6.4 --- Crash Fault Tolerance --- p.35 / Chapter 6.5 --- Implementation --- p.36 / Chapter 7 --- Evaluation of CFTDedup --- p.37 / Chapter 7.1 --- Setup --- p.37 / Chapter 7.2 --- Experiment 1 (Archival) --- p.38 / Chapter 7.3 --- Experiment 2 (Restore) --- p.39 / Chapter 7.4 --- Experiment 3 (Recovery) --- p.40 / Chapter 7.5 --- Summary --- p.41 / Chapter 8 --- Future work and Conclusions of CFTDedup --- p.43 / Chapter 8.1 --- Future Work --- p.43 / Chapter 8.2 --- Conclusions --- p.44 / Chapter 9 --- Conclusion --- p.45 / Bibliography --- p.47