藉由霧聯網來延伸物聯網平台的可擴充性

Abstract

由於聯網的裝置越來越多，佈建在雲端系統中的物聯網平台的流量負載也日益嚴重，雖然這種過度負載的情形可由增加雲端系統裡的資源來解決，本研究提出一個用霧計算(Fog Computing) 來解決壅塞的另類方案。 霧計算不但可以用來解決雲端系統的壅塞問題，也可提供關鍵服務所需要的低延遲反應。 在本研究中，我們首先將oneM2M平台遷移到霧計算架構中，並提出一個分層式容器化的oneM2M中間節點架構。並在此架構下設計了一種機制，來提高物聯網平台的可擴充性。在此論文中，我們說明了我們的系統設計並以工業4.0為例子展示了我們系統的高度擴充性。最後我們比較了我們所設計的動態擴充機制和靜態資源管理在效益上的不同。

As more and more IoT/M2M devices are connected to the Internet, the IoT/M2M platforms normally deployed in the Cloud are increasingly overloaded with a large amount of data traffic. Though more resources in the cloud may be allocated to alleviate such overloading issues, this research proposes the alternative of utilizing Fog computing to extend the scalability of IoT/M2M platforms in the cloud. The Fog is used not only to offload the over congested cloud but also to provide low latency required by critical applications. Our first step is to migrate oneM2M, a global IoT/M2M platform, to a Fog computing architecture in which the middle nodes of oneM2M are organized into a highly scalable hierarchical container-based Fog nodes. We then design a mechanism to dynamically scale in/out the serving instances of the middle nodes in order to make the whole IoT/M2M platform more scalable. In this thesis, we illustrate our system design and demonstrate its scalability capacity with an industrial IoT (IIoT) use case. Finally, we compare the performance of our dynamic scaling mechanism with those based on a static and fixed pool of serving instances.