邊界運算將資料的計算和儲存單元移動到接近資料來源的地方，因此邊界運算可以預先處理資料以減少傳送到雲端資料中心的資料量並降低雲端的負載。在邊界運算中，虛擬模組的配置是一個很重要的議題，因為模組的配置對整個系統的運作效能和硬體資源的使用率有很大的影響。在本篇論文中，我們探討在邊界運算平台中的模組配置問題，我們將此問題公式化成一整數的非線性規劃問題，目標是最大化滿足使用者的需求，而此問題會考慮到裝置的頻寬和儲存限制。由於此問題屬於NP-hard的問題，我們提出一個能在多項式時間內得到解決的演算法，此演算法基於鬆弛(Relaxation)和化整(Rounding)的技巧來解決此規劃問題。根據模擬結果顯示，我們的演算法相較於其他方法能滿足更多的使用者需求。

Edge computing refers to data storage and processing at the edge of network instead of cloud data centers. In edge computing, user data can be preprocessed to reduce the network traffic and load of the cloud system. Module deployment scheme is vital in edge computing since it has a significant effect on the performance and the resource utilization of the edge computing system. We formulate the module deployment as an integer nonlinear programming problem. Our objective is to maximize satisfied user requests under the constraints of limited communication bandwidth and storage capacity of devices where the modules are deployed. Since the optimization problem is NP-hard, we propose a polynomial time algorithm based on relaxation and rounding techniques to solve this problem. The simulation results show that our algorithm satisfies more user requests than other benchmark algorithms.

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