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Author: 謝宗諺
Tsung-Yen Hsieh
Thesis Title: 四層聯合架構中納入多重伺服器故障考量之卸載: 容錯設計、分析、最佳化及系統動態探究
Incorporation of Multi-Server Failures into the Offloading of a 4-Tier Federated Architecture: Fault Tolerance Design, Analysis, Optimization, and System Dynamics Exploration
Advisor: 馮輝文
Huei-Wen Ferng
Committee: 魏宏宇
Hung-Yu Wei
鄭傑
Jay Cheng
黎明富
Ming-Fu Li
胡誌麟
Chih-Lin Hu
Degree: 碩士
Master
Department: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
Thesis Publication Year: 2022
Graduation Academic Year: 110
Language: 中文
Pages: 126
Keywords (in Chinese): 多接取邊緣運算行動雲端運算車輛霧端運算工作卸載服務品質違反機率
Keywords (in other languages): Multi-access Edge Computing, Mobile Cloud Computing, Vehicular-Fog, Offloading, QoS Violation Probability
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  • 物聯網 (Internet of Things, IoT) 的興起及智能車輛 (Smart Vehicle) 的發展和使用者裝置 (User Equipment) 的普及為使用者提供多樣的服務,然而,其中不乏有需要大量計算的應用程式,例如:增強/虛擬現實 (AR/VR)、線上遊戲,這些應用程式會產生巨量計算,導致使用者裝置電力的快速消耗。為此,有卸載 (Offloading)機制的提出,使用者裝置將自身的任務卸載到計算資源比較豐富的雲端伺服器(Cloud Server)、邊緣伺服器 (Edge Server) 或車輛霧 (Vehicular Fog),以減少使用者裝置的計算量,並減少能源消耗 (Energy Consumption) 和等待時間 (Waiting Time)。
    然而,在過往的論文中,大多假設伺服器不會故障 [1],鮮少討論到伺服器會故障的問題,特別是多重伺服器故障問題。因此,本論文將考量 [1] 的架構,進一步討論雲端伺服器、邊緣伺服器、車輛霧之故障容錯設計並分析卸載延遲等效能指標。於本論文中,我們提出幾種容錯設計,並獲得其理論效能分析及最佳化之參數。理論效能分析透過模擬驗證後,不同容錯機制間之效能比較與相關系統動態探究將予以呈現與觀察,以利找出本論文所提且最為推薦之容錯設計。


    The rise of the Internet of things (IoT) and the development and application of smart vehicles offer a variety of services for user equipments. However, there are many computingintensive applications, such as augmented/virtual reality (AR/VR), online games, etc.
    These applications will generate massive amounts of computation and power consumption rapidly on UEs. For solving such an issue, offloading has been proposed. A UE can
    offload its own tasks to the server, such as the cloud server, the edge server or the vehicular fog to reduce the computational load, power consumption, and waiting time of the UE.
    However, most of past papers, e.g. [1], assumed that the server will not breakdown, and rarely discussed the problem of server failures, especially the problem of multiple-server failures. Therefore, this paper will consider the architecture of [1] to further incorporate the fault-tolerant design for cloud servers, edge servers, and the vehicle fog first and then analyze the offloading delay accordingly. In this paper, we shall propose several fault-tolerant offloading mechanisms, and obtain their performance measures and optimized parameters in a theoretical apporach. After the theoretical performance analysis is verified by simulation results, the performance comparison among different fault-tolerant offloading mechanisms and the system dynamic exploration presented and observed in order to facilitate the most recommended design of the fault-tolerant offloading proposed by this paper.

    論文指導教授推薦書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 考試委員審定書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 中文摘要 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii 英文摘要 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 誌謝 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v 目錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 表目錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix 圖目錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x 第一章、緒論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 研究背景與技術 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 行動雲端運算 (Mobile Cloud Computing, MCC) . . . . . . . . . . . . . 1 1.3 多接取邊緣運算 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.4 車輛霧端運算 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.5 工作卸載 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.6 研究動機 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.7 論文組織 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 第二章、相關文獻探討 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1 單一資源之卸載文獻回顧 . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 混合資源之卸載文獻回顧 . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 卸載中伺服器故障之文獻回顧 . . . . . . . . . . . . . . . . . . . . . . 9 2.4 與相近論文之比較及本論文之貢獻 . . . . . . . . . . . . . . . . . . . 10 第三章、系統架構與具容錯設計之卸載機制 . . . . . . . . . . . . . . . . . . . 11 3.1 環境架構 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.2 方法設計 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2.1 MCMV-FR 方法設計 . . . . . . . . . . . . . . . . . . . . . . . 15 3.2.2 MCMV-QR 方法設計 . . . . . . . . . . . . . . . . . . . . . . . 19 3.2.3 MCMV-SE 方法設計 . . . . . . . . . . . . . . . . . . . . . . . 23 3.2.4 MCMV-OE-F 方法設計 . . . . . . . . . . . . . . . . . . . . . . 27 第四章、系統架構效能分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 4.1 服務品質違反機率分析 . . . . . . . . . . . . . . . . . . . . . . . . . . 29 4.1.1 MCMV-FR 服務品質違反機率分析 . . . . . . . . . . . . . . . 31 4.1.2 MCMV-QR 服務品質違反機率分析 . . . . . . . . . . . . . . . 35 4.1.3 MCMV-SE 服務品質違反機率分析 . . . . . . . . . . . . . . . 41 4.2 平均工作延遲分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.2.1 MCMV-FR 工作延遲分析 . . . . . . . . . . . . . . . . . . . . . 49 4.2.2 MCMV-QR 工作延遲分析 . . . . . . . . . . . . . . . . . . . . 50 4.2.3 MCMV-SE 工作延遲分析 . . . . . . . . . . . . . . . . . . . . . 52 4.3 工作遺失機率分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.3.1 MCMV-FR 工作遺失機率 . . . . . . . . . . . . . . . . . . . . . 56 4.3.2 MCMV-QR 工作遺失機率 . . . . . . . . . . . . . . . . . . . . 57 4.4 平均服務停止時間 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 4.4.1 MCMV-FR 服務停止時間 . . . . . . . . . . . . . . . . . . . . . 59 4.4.2 MCMV-QR 服務停止時間 . . . . . . . . . . . . . . . . . . . . 60 第五章、模擬結果數值討論與分析 . . . . . . . . . . . . . . . . . . . . . . . . 62 5.1 模擬與數值討論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.2 環境參數設定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.2.1 公平機制下不同數量之雲端伺服器 nC 之影響 . . . . . . . . . 63 5.2.2 累加機制下不同數量之雲端伺服器 nC 之影響 . . . . . . . . . 66 5.2.3 不同雲端伺服器容量之影響 . . . . . . . . . . . . . . . . . . . 68 5.3 不同邊緣伺服器容量之影響 . . . . . . . . . . . . . . . . . . . . . . . 73 5.4 不同工作抵達率之影響 . . . . . . . . . . . . . . . . . . . . . . . . . . 75 第六章、結論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 參考文獻 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 附錄 A:服務品質違反機率 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 附錄 B:所採用之 MPE (Main Probability Estimation Algorithm) 跟 SPE (SubProbability Estimation Algorithm) . . . . . . . . . . . . . . . . . . . . . . 98 附錄 C:不同機制之平均工作延遲 . . . . . . . . . . . . . . . . . . . . . . . . . 101 附錄 D:Beta 分布特例下之推導結果 . . . . . . . . . . . . . . . . . . . . . . . 112

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