隨著智慧聯網(IoT)的應用蓬勃發展，越來越多機器對機器(M2M)的裝置被布置在社會中，在眾多M2M的應用中特別是視頻監視系統被廣泛的討論，長期演進技術(LTE)是新一代行動網路的主流，可以提供高傳輸速率以及更高的網路容量，也因此對M2M視頻監視系統來說LTE是一個絕佳的傳輸標準。在這篇論文中，我們研究一個在LTE之視頻監視系統的監視品質最大化的問題，假設環境中一定數量的物體以及一定數量的攝影機，每個攝影機都擁有自己的監視品質以及覆蓋範圍，我們目標是要透過分配LTE有限的資源給攝影機讓整個環境中的物體都能被友給予資源的攝影機覆蓋到並且最大化整個系統的監視品質，我們提出一個方法來選擇攝影機以及要被分配的資源，另外為了因應網路狀況並減少LTE網路的負擔，我們提出一個動態調整的方法來調整我們的分配狀況。

Due to the proliferation of applications for the Internet of Things, an increasing number of machine to machine (M2M) devices are being deployed. In particular, one of the M2M applications, video surveillance, has been widely discussed. Long Term Evolution (LTE), which can provide a high rate of data transmission and wide range of coverage, is a promising standard to serve as an M2M video surveillance system. In this thesis, we studied a performance maximization problem in an LTE video surveillance system. Given a set of objects and a set of cameras, each camera has its own performance grade and its own coverage. The goal is to maximize the performance of the system by allocating limited resources to cameras while all objects should be monitored by the selected cameras. We propose a heuristic method to select the cameras and allocate resources to them to solve the problem. Moreover, to reduce the load of the LTE system, a dynamic adjustment method is also proposed.

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