近幾年來，隨著雲端運算的普及且有越來越流行的趨勢，像是大數據的雲端運算應用程式需要一個更大的網路頻寬且強而有力的大型資料網路中心。而為了因應這些需求，現在有越來越多的學者提出不同的大型資料網路中心拓樸來解決這些問題。在其中BCube是一個著名的遞迴式定義結構的拓樸，它有著良好的拓樸特性，像是對伺服器彼此間提供了多條短距離的平行路徑，或是針對在伺服器和交換器的容錯上允許某些鏈結斷掉時，不會大幅降低整體的頻寬效能。在原作者提出的分散式路由BSR演算法，由每個來源伺服器去計算和決定它傳送資料給目的伺服器的路徑，這種演算法實作簡單且快速，不過在彼此伺服器相互傳送資料而不去考慮彼此選擇的路徑，在最差的狀況下，它們可能有很高的機率在使用相同的路徑而發生碰撞，導致浪費了將近百分之五十原本BCube拓樸每條鏈結能提供的頻寬。因此在這篇論文，為了去改善傳遞資料時在BCube上大量的碰撞和充分利用到每條鏈結的頻寬，我們在BCube拓樸上增加了一個全域的集中管理伺服器和設計一個在這台伺服器上執行的集中式動態流配置的平行演算法: CDPFS 和CDPFSMP 分別針對伺服器彼此間的單一路徑和多條路徑來分配資料流。我們提出的演算法主要是透過在BCube上蒐集到的每個網路流的可用路徑，並同時計算較不壅塞的可用路徑來優先分配給每個網路流。在模擬實驗的結果顯示，我們提出的集中式演算法可以充分利用BCube良好的拓樸特性和提升整體效能對每個網路流在BCube上的負載平衡。

In recent years, with the growing popularity of cloud computing, big-data applications increase demands for large and powerful data center networks (DCNs). There are more and more newly proposed network topologies for DCNs. BCube is a well-known recursively defined network structure which has good properties providing multiple low-diameter paths and good fault-tolerance for data center networks. Its distributed routing algorithm BSR which is fast and easy to build multiple parallel path set. But in the worst case, it may occur many flow collisions and waste 50\% capacity of each link in BCube. In this paper, in order to fully use those redundant links and improve load balancing in BCube, we add the central master computer to BCube topology and design a centralized dynamic parallel flow scheduling algorithm: CDPFS and CDPFSMP for single-path and multi-paths. We mainly focus on finding the least congestion path for each flow with global network status information and allocate those paths to each flow in parallel. The simulation result shows that our proposed algorithms which take advantage of BCube structure and give a good performance for load balancing.

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