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dc.contributorYen-Chieh Ouyangen_US
dc.contributor.authorYi-Ju Chiangen_US
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dc.description.abstract隨著雲端服務平台的日益普及,在服務系統中如何進行資源配置與任務調度來維持服務水平是服務供應商面臨的主要挑戰之一。在論文中針對雲端系統資源配置、省電運作模式與任務調度機制進行了探討與分析。首先在系統阻擋率與任務響應時間的性能約束下,研究與設計有效地資源配置與省電機制來穩定服務水平與降低系統耗能。在論文中,我們根據不同的系統容量、資源配置與使用者行為來建立不同的分析模型,並利用排隊理論,分析系統容量對任務丟失率與系統性能的影響。在不同系統根據所需考慮的運作成本、系統耗能與性能要求,分別設置不同的目標函數與性能約束條件。在不同的省電機制下研究對於響應時間、運作狀態與運作成本的影響。我們所提出的演算法與三種省電運作模式能有效地進行資源配置、降低伺服器在閒置狀態下的耗能成本,並能在性能約束條件下求最佳解。 接著進一步探討當系統處在高負載的狀態時,如何在負載的限制下進行最佳的任務調度。在雲端服務系統中,開發任務調度機制的主要目標是降低任務的響應時間,讓任務能在處理期限內完成,同時進行壅塞控制,避免系統過載。最後我們所設計的方法和其他方法進行模擬比較,證明能夠改善系統性能與利潤。zh_TW
dc.description.abstractAs cloud computing become more and more popular, how to manage resource provisioning and schedule tasks are several critical challenges for cloud providers. To analyze these issues, resources provisioning, power-saving policies and task scheduling in cloud computing are studied and analyzed in this research. First of all, we try to design an effectively resources provisioning mechanism and power-saving policies according to system blocking probability and response time constraints, so as to meet performance guarantees and reduce power consumption. Different models are designed according to various system capacities, resources provisioning and user behaviors. The relationship between system capacity and task loss rates is analyzed based on different queuing models and system performance. According to incurred cost, power consumption and system performance, different objective functions with performance guarantees are proposed. The effect of energy-efficiency controls on response times, operating modes and incurred cost are demonstrated. Three power-saving policies are proposed to reduce idle power consumption, manage resources provisioning and solve the optimal solutions under a performance constraint. Furthermore, how to develop an optimal task scheduling approach when the system is under heavy load is studied. The main purpose is to reduce response time, so as to make tasks complete within their deadline constraints. Simulation results show that the proposed approach outperforms other approaches in terms of system performance and profit.en_US
dc.description.tableofcontentsAbstract.........ii Contents.........iii List of Figures........v List of Tables.........vii Chapter 1 Introduction.....1 1.1 Background and Motivation.....1 1.2 Literature Review...5 1.2.1 Analysis of Capacity Provisioning.5. 1.2.2 Workload Control ........................7 Chapter 2 Cloud Service Models.........10 2.1 Service System with Different Buffer Sizes....10 2.1.1 A Multi-Servers System with Blocking Control..10 2.1.2 Performance Evaluation......13 2.1.3 Resources Provisioning Scheme....16 2.2 Performance Analysis............21 2.2.1 Experimental Results..........21 2.2.2 Comparison of Results.........25 2.3 Energy-Efficiency Controls......29 2.3.1 Related Works.....29 2.3.2 ISN Policy.....33 2.3.3 SN and SI Policies.....35 2.3.4 Queuing Models....38 Chapter 3 Optimization Problem Formulation.....43 3.1 Operational Cost................43 3.2 Performance Comparisons and the ECG Algorithm..........................................46 Chapter 4 Numerical Validation.....54 4.1 Experiments Results......54 4.2 Comparison of Results.....58 Chapter 5 Task Scheduling.....62 5.1 Scheduling Approaches.....62 5.2 Load-Based Scheduling Approach.....69 5.3 Experimental Environment......72 Chapter 6 Conclusion.....80 6.1 Conclusion.....80 Reference......82 Publication List.....90zh_TW
dc.subjectQueuing theoryen_US
dc.subjectsystem blocking probabilityen_US
dc.subjectpower-saving policiesen_US
dc.subjecttask schedulingen_US
dc.titleTask Scheduling Mechanism and Resources Provisioning Management in Cloud Computing Systemsen_US
dc.typethesis and dissertationen_US
item.openairetypethesis and dissertation-
item.fulltextwith fulltext-
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