近年來，隨著雲端服務的用戶數量和所需資源顯著增加，對於網路供應商來說，提供一個低延遲和低成本的強健網絡架構已經成為一個巨大的挑戰。在雲端資料中心網路的路由演算法中，擁塞控制是至關重要的課題之一。在本篇碩士論文中，我們提出了一種在BCube雲端資料中心中應用加權最短路徑之擁塞控制路由演算法WSPR。WSPR可以提前防止擁塞，從而充分利用空閒的網絡資源。我們選擇 BCube 作為我們的網絡模型並修改網絡拓撲，以使用軟體定義網絡的概念來獲得拓撲的完整概觀。首先，我們設計包含來源伺服器和目標伺服器之間所有最短路徑的SP圖。其次，使用本碩士論文提出的WSPR演算法為每個資料流分配最合適的路徑以達到擁塞控制。我們建構了一個模擬資料中心的系統，並將WSPR與其他經典方法進行比較評估。模擬實驗結果顯示在所有比較方法中，我們提出的WSPR演算法在最大延遲、平均延遲和吞吐量方面具有最佳性能。

Cloud services are experiencing a remarkable increase in the number of users and the resource required over the past few years. As a result, it has become a great challenge for the internet vendors to make a robust framework to serve the customers with low cost and delay. Congestion control is one of the essential topics of routing algorithms in cloud data center networks. In this thesis, we propose a weighted optimal scheduling algorithm WSPR for congestion control in cloud data center networks which prevents congestion in advance with the global view so that it can make good use of vacant network resources. We choose BCube as our network model and modify the network topology to fit software-defined networks so as to have a full view of the topology. First, we design the SP graph which contains all shortest paths between a source server and a destination server. Second, we propose WSPR to allocate the most appropriate path to each flow for congestion control. We implement a system to simulate a data center, and evaluate our proposed algorithm WSPR by comparing WSPR with other classical methods. The experimental results demonstrate that our proposed algorithm WSPR has the best performance in terms of the maximum delay, average delay, and throughput among all compared methods.

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