摘要
近幾年來在分散式運算當中的霧運算領域有許多有趣的應用，霧運算是一種新的運算架構，延伸自雲端運算，其主要目標是解決物聯網當中延遲敏感及位置感知的問題，雖然有許多基於霧運算的理論和應用被提出，但大多數都只是用模擬的方式來評估他們的架構，離真實情況仍有一段距離。基於上述理由，本論文的目標是提出一個用戶端-霧-雲 (client-fog-cloud) 的多層資料處理及彙整框架，這框架適用於延遲敏感的應用，並且為了滿足在物聯網當中的以下需求：廣泛分散、大量上傳、低延遲、即時互動。以兒童走失警報服務來當作實際場景，用來評估本論文所提出的架構，並用與傳統的雲端運算架構來比較效能，結果顯示我們的架構能減少32%的反應時間(response time)及減少30%的總共要上傳到雲端的資料量。
並列摘要
Recently years, there are a lot of interests in fog computing in the distributing computing field. Fog computing is a new computing architecture extended from cloud computing, and proposed to solve problems met on latency-sensitive and location-awareness IoT services. Although there are several fog computing-based theories and applications have been proposed, most of them only evaluated their works by theoretical simulations. Those are far from real situations and difficult to be applied into practice. Motivated by previous works, this study is aimed to propose a client-fog-cloud multilayer data processing and aggregation framework, based on fog computing paradigm. The proposed framework is designed to help latency-sensitive applications in IOT context, which meet requirements: widely distribution, massive uploading, low latency, and real-time interaction. Authors used the child abduction alert service as a sample to evaluate the proposed framework in practical scenarios, and compare performance and feasibility to the conventional cloud solution. Results showed that this framework can reduce about 32% response time and 30% data transferred to the cloud.