現今, 許多企業內部會使用大型資料網路中心來提供許多各式各樣的服務，從網路服務到線上遊戲等等，現在大型企業所用的資料網路中心都是使用fat-tree作為拓樸架構，fat-tree是使用多的根頂點所組成的一種階層式樹狀架構，這種架構不僅可以達到點對點之間的多個路徑，還可以提升階層跟階層之間的頻寬，然而，由資料網路中心所提供的任何網路服務，它的效能好壞跟資料網路中心所使用的路由協定有很大的關係，而一般傳統網路所使用的路由都是以最短路徑作為最佳考量，很明顯的，這並不適用在資料網路中心，原因在於資料網路中心是以多重路徑的概念為主軸出發，而若使用一般的路由協定用資料中心，很容易造成資料傳送在某一個鏈結上形成壅塞，而其他鏈結卻沒什麼資料傳送，這現象會造成網路資料中心的效能大大降低，另外一個重要議題是如何在多重路徑的情況下達到負載平衡，一般的路由協定很容易造成壅塞，而即使使用支援多重路徑的路由協定(例如以靜態方法)，若沒有根據網路流量的情況來調配每個路由的路徑，也會很容易造成網路壅塞，大大降低效率，根據這些原因，我們提出了以基因演算法為主軸的動態負載平衡路由演算法，這種演算法是一種探索式演算法並且是以集中式管理的方式達到動態負載平衡流量控制，我們的演算法主要是用Mininet模擬器建造拓樸並用OpenFlow 控制式ryu來實作動態平衡演算法

Modern data center networks for fat-tree topology usually adopt multi-rooted hierarchical tree structure in order to achieve multiple paths capability and increase bisection bandwidth. However, the performance of data center networks heavily depend on routing protocols. Traditional routing protocols are not suitable for modern data center topology because of the lack of multiple paths routing support. Another important issue in data center networks is load-balancing. Due to some static routing protocols limitation, that could lead to some links are overload or underload utilization. This situation could largely reduce the the performance of data center networks. For these reasons, we present a GA-based dynamic load-balancing routing algorithm which is heuristic and with centralized scheduling technique. The GA-based routing algorithm mainly use genetic algorithm to search the optimization solutions. We implement our algorithm in OpenFlow controller Ryu and Mininet emulator, which is based on Software Defined Networking (SDN) architecture. The evaluation results show that our algorithm can effectively achieve load-balancing and increase bisection bandwidth.

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