Author: |
江岳亭 Yueh-Ting Chiang |
---|---|
Thesis Title: |
在雲、邊緣、使用者裝置聯合系統中考慮邊緣伺服器故障之卸載: 設計、分析與最佳化 Offloading in the Cloud, Edge, and UE Federated System with Consideration of Edge Server Failure: Design, Analysis, and Optimization |
Advisor: |
馮輝文
Huei-Wen Ferng |
Committee: |
馮輝文
Huei-Wen Ferng 范欽雄 Chin-Shyurng Fahn 葉生正 Sheng-Cheng Yeh 郭芳璋 Fang‑Chang Kuo |
Degree: |
碩士 Master |
Department: |
電資學院 - 資訊工程系 Department of Computer Science and Information Engineering |
Thesis Publication Year: | 2021 |
Graduation Academic Year: | 109 |
Language: | 中文 |
Pages: | 172 |
Keywords (in Chinese): | 工作卸載 、邊緣伺服器故障 、服務品質違反機率 、多接取邊緣運算 、最佳化 |
Keywords (in other languages): | Task Offloading, Edge Server Failure, QoS Violation Probability, Multi-Access Edge Computing, Optimization |
Reference times: | Clicks: 1099 Downloads: 1 |
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工作卸載 (Task Offloading) 是多接取邊緣運算 (Multi-Access Edge Computing, MEC) 的一項關鍵技術,此項技術透過將使用者裝置 (User Equipment, UE)產生的工作卸載到其他資源更豐富的伺服器,以解決行動設備硬體條件不足及資源有限的問題。工作卸載能降低行動設備的工作處理時間,並減少電量的消耗。 目前工作卸載之研究大部分考慮如何最小化工作的延遲,少數研究考量工作延 遲的門檻限制; 另一方面,過去與工作卸載之研究均假設伺服器不會發生故障。因此,本論文除了同時針對工作延遲是否超過門檻做考量,更進一步考量邊緣 伺服器故障率是否超過門檻,以達更周延之考量; 並設計當邊緣伺服器故障時的 五種解決機制,第一種是替 [1] 考量邊緣伺服器故障所設計的一種基準機制,第 二、三種是則以 Wu 等人 [2] 的概念做延伸而設計之兩種機制,最後兩種方法為本論文全新提出的機制,採用備用伺服器,以解決主邊緣伺服器故障的問題。針對此五種機制,相關之數理分析均將提供,以利做最佳化之問題形成 (Problem Formulation)。在模擬驗證數理分析後,透過數理分析可獲大量之數值觀察與討論,我們全新提出的兩種機制相較於其他機制,更能滿足服務品質 (Quality of Service, QoS) 表現優越,最為被推薦使用。
Task offloading is a key technology of multi-access edge computing (MEC). This technology solves the problem of the user equipment (UE) with limited resources by offloading its tasks to the other servers with more resources. Task offloading can reduce the task delay of mobile devices and reduce the power consumption. Up to now, many studies consider how to minimize the task delay simply without consider whether the task delay has exceeded its associated threshold or not. On the other hand, those studies assume that the servers will not collapse. Therefore, this thesis will focus on whether the task delay exceeds its associated threshold and whether the edge server failure rate exceeds its associated threshold. Towards this goal, five schemes to solve the offloading problem with the edge server failure are to be proposed. The first one serves a benchmark mechanism designed for this issue extending the concept of \cite{hwang2021offloading} Two schemes are designed for this issue by extending the concept of \cite{wu2018performance}. As for the remaining two schemes are the brand new schemes by utilize the spare/dispatch edge server for this issue. For these five schemes, the corresponding mathematical analysis will be done to facilitate the corresponding optimization problem. After validation by simulations, our mathematical analysis afford extensive numerical results and observation to successfully demonstrate that our two brand new proposed schemes are more capable of satisfying the quality of service (QoS) than the other schemes and are highly recommended for use
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