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Access-pattern-aware data management in cloud platforms / CUHK electronic theses & dissertations collection

Database outsourcing is an emerging paradigm for data management in which data are stored in third-party servers. With the advance of cloud computing, database outsourcing has become popular and highly adopted. However, as a result, many technology challenges have arisen. / In this thesis, we study two problems with respect to the challenges, and propose solutions for each problem with the consideration of access patterns. The first problem is raised from theviewpoint of service providers. We study the problem of data allocation in scalable distributed database systems for achieving the high availability feature of cloud services. We propose a data allocation algorithm, which makes use of time series models from previous access patterns to perform load forecasting and reallocate data fragments to balance the workload within the system. Simulation results show that, with accurate forecasting, the proposed algorithm gives a better performance than general threshold-based algorithms. / The second problem addresses the clients' concern that service providers may not be trustworthy. We first illustrate how service providers can infer sensitive information through query access patterns even when data are encrypted. Then, we propose techniques that break down large queries and randomize query access patterns such that service providers cannot infer sensitive information with a high degree of certainty. Experiments on benchmark data show that a high level of access privacy can be achieved by the proposed techniques with a reasonable overhead. / 數據庫外包是近年新興的一種數據管理服務,其特點是數據儲存於第三方的伺服器內。隨著雲端科技的發展,數據庫外包服務日趨普及,同時亦產生不少技術問題。 / 本文著重探討兩個問題。首先,從服務供應商的角度研究可擴展的分布式數據庫系統如何分配數據來提供高可用性的雲端服務。鑑於用戶訪問模式會隨著時間轉變,我們提出以時間序列模型預測負荷的算法重新分配數據,以平衡系統的工作量。通過模擬實驗可知在準確的負荷預測下,我們提出的算法比基於闆值的算法有更好的表現。 / 第二個探討的問題是如何保障用戶私隱,避免洩露給服務供應商。文中列舉了數據加密的情況下,服務供應商如何通過分析用戶訪問模式獲取資料,進而提出相應的保障技術。透過用戶訪問模式的隨機化,能使服務供應商無法準確比對用戶的資料。基準數據實驗指出此項技術可有效保護私隱,而且不會對訪問速度造成太大影響。 / Li, Shun Pun. / Thesis M.Phil. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 86-93). / Abstracts also in Chinese. / Title from PDF title page (viewed on 11, October, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_1291497
Date January 2015
ContributorsLi, Shun Pun (author.), Wong, Man Hon (thesis advisor.), Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. (degree granting institution.)
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography, text
Formatelectronic resource, electronic resource, remote, 1 online resource (x, 95 leaves) : illustrations, computer, online resource
RightsUse of this resource is governed by the terms and conditions of the Creative Commons "Attribution-NonCommercial-NoDerivatives 4.0 International" License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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