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研究生:蔡沐容 
研究生(外文):Mu-Jung Tsai
論文名稱:以降低成本為目標同時考量執行時間變動及服務品質條件之複合式雲端服務組成模組選擇問題之研究
論文名稱(外文):QoS-driven Service Selection Methods for Cost Minimization of Composite Cloud Services under Stochastic Runtime Performance
指導教授:黃國展黃國展引用關係
指導教授(外文):Kuo-Chan Huang
口試委員:黃國展張西亞楊朝棟陳隆彬賴冠州
口試委員(外文):Kuo-Chan HuangChang Hsi YaYang Ch'ao TungCh'ên Lung PinLai Kuan Chou
口試日期:2014-07-10
學位類別:碩士
校院名稱:國立臺中教育大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:英文
論文頁數:49
中文關鍵詞:複合式雲端服務服務選擇成本最佳化動態服務品質
外文關鍵詞:composite cloud serviceservice selectioncost minimizationStochastic QoS
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近年來,雲端計算已經成為最有前景的下一代計算平台。以軟體即服務(Saas)和服務導向架構(SOA)為基礎的複合式雲端服務,正在改變我們開發和使用軟體的方式,並預期將為軟體開發者及使用者帶來極大的便利和效益。雲端服務提供者在組合一個複合式雲端服務時,必須面臨服務選擇的問題。服務選擇可看成是一個限制條件下的最佳化問題,目的是要在盡量符合服務層級協議(SLA)的前提下,達到降低成本的目標。這樣的一個服務選擇問題若考量實際雲端環境中服務的執行效能等服務品質指標之可能的動態變化,將變得更難處理。本篇論文提出了兩個不同的方法來解決上述之動態雲端環境下的服務選擇問題。第一個方法以循環的方式,反覆執行三個步驟: 以整數線性規劃為基礎之最佳化求解、模擬動態雲端環境的影響、服務選擇調整,直到挑選出最佳服務組合為止。第二個方法則利用了統計學上的Chebyshev定理並搭配了非線性規劃求解來處理服務選擇的問題。這個方法將服務執行效能的動態變化因素直接納進非線性規劃目標函數的考量當中,因此使用單一步驟就可處理服務選擇問題。我們進行了一系列的模擬實驗來評估及比較我們所提出的方法。實驗結果顯示我們的方法比起先前文獻中的方法,更能夠有效地降低提供複合式雲端服務所需的總成本。
Cloud computing has become the most promising next-generation computing platform recently. Composite cloud services based on the methodologies of Software as a Service (SaaS ) and Service-Oriented Architecture (SOA) are transforming how people develop and use software and expected to bring a lot of benefits for both software developers and users. Cloud service providers have to deal with the issues of service selection when composing a composite cloud service, which can be viewed as a constrained optimization problem aiming to minimize the total costs of providing such services with respect to the constraints of Service Level Agreement (SLA). The service selection problem becomes even more challenging when considering the stochastic QoS performance. This thesis presents two approaches to the service selection problem in dynamic cloud environments where services’ performance might varies with time. The first one is an iterative compound approach, with each iteration containing three steps: Integer Linear Programming (ILP) optimization, simulation of stochastic performance, and adaptation. The second approach is a one-step method based on the Chebyshev’s theorem and nonlinear programming. It takes into consideration the stochastic performance in the objective function of a nonlinear programming formulation. We have conducted a series of simulation experiments to evaluate the proposed approaches. Our approaches outperform the previous method in the literature significantly in terms of total cost reduction.
誌謝Ⅰ
摘要Ⅱ
AbstractⅢ
Table of ContentsⅣ
List of FiguresⅤ
List of TablesⅦ
Chapter 1. Introduction 1
Chapter 2. Related Work 5
Chapter 3. Service Selection under Stochastic Performance 9
3.1 Composite Cloud Services 9
3.2 An Iterative Compound Approach 11
3.3 One-Step Statistics-Based Nonlinear Optimization 16
Chapter 4. Experiments and Performance Evaluation 20
4.1 Experimental Setup 20
4.2 Performance Results 20
Chapter 5. Conclusions and Future Work 33
References 35

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