隨著物聯網和移動設備的快速發展，許多設備的計算能力和電池壽命成為了限制其性能的主要瓶頸，工作卸載 (Task Offloading) 被認為是一種能有效解決這些問題的方法，旨在提升智慧運輸系統及其他應用中的效能和可靠性。本碩士論文考慮了異質環境 (Heterogeneous Environment)，且伺服器會有故障的情況，基於 [1] 的卸載架構，在雲端 (Cloud)、邊緣 (Edge) 與車輛霧 (Vehicular Fog) 之外，添加了鄰近裝置 (Surrounding Equipment)，將使用者裝置 (User Equipment) 較相近的運算資源納入架構中，本研究提出了三種容錯卸載設計，在每種模式下根據這些鄰近資源的可用性，依照關聯向量 (Association Vector) 的不同，將可能出現之子情境納入，並在含有故障的情境下分別設計對應的處理策略，可在整體範圍中分配出不同的裝置數量，也提出最佳化問題來找尋最佳卸載機率。本論文分析了每個子情境下的故障處理策略，並透過模擬驗證這些策略的表現，比較不同資源狀態下的服務品質違反機率和平均工作延遲，來探討系統如何能在複雜的情境下維持一定效能，最後從實驗結果中可觀察到更多的系統動態 (System Dynamics)，因此與先前研究相比，本論文之卸載設計更適合應用於實際的網路情景。

With the rapid development of the Internet of Things (IoT) and mobile devices, the computing power and battery life of many devices have become major bottlenecks that limit their performance. Task offloading is considered an effective method to address these issues, aiming to improve the efficiency and reliability of intelligent transportation systems and other applications. This thesis considers a heterogeneous environment in which servers may fail, and based on the offloading framework from [1], it incorporates surrounding equipment into the architecture, alongside the cloud, edge, and vehicular fog, to include computing resources that are closer to the user equipment. This research proposes three fault-tolerant offloading designs. In each model, depending on the availability of these surrounding resources and the different association vectors, potential sub-scenarios are considered, and corresponding handling strategies are designed for scenarios that involve failures. The design allows for the allocation of different numbers of devices across the entire scope, and an optimization problem is proposed to find the optimal offloading probability. This thesis analyzes the fault-handling strategies under each sub-scenario and validates the performance of these strategies through simulations. By comparing the quality of service violation probability and average task delay under different resource conditions, the study explores how the system can maintain a certain level of performance in complex situations. Finally, from the experimental results, more system dynamics can be observed, making the offloading design in this thesis more suitable for practical network scenarios compared to previous research.

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