【摘要】：隨著“云”概念的興起,云存儲、云計算、云視頻、云安全等云服務(wù)成為了炙手可熱的紅人。而在這股云浪潮的背后,則是各大云服務(wù)提供商建立的大型數(shù)據(jù)中心,通過成千上萬的服務(wù)器組成集群,配套對應(yīng)的存儲系統(tǒng)、網(wǎng)絡(luò)互連設(shè)備等各種要素,借助虛擬化的手段充分利用計算、存儲和網(wǎng)絡(luò)等各類資源。在規(guī)模如此龐大的數(shù)據(jù)中心內(nèi)部每個服務(wù)器實(shí)例隨時都有可能有各種不同應(yīng)用向網(wǎng)絡(luò)中注入流量,如何將內(nèi)部巨大的負(fù)載進(jìn)行均衡使網(wǎng)絡(luò)資源得到充分利用是個亟待解決的問題。 OpenFlow技術(shù)源于斯坦福大學(xué)的一個研究性項目,后逐步發(fā)展成為SDN的概念,而OpenFlow自然成為了SDN使用最廣泛的網(wǎng)絡(luò)協(xié)議。OpenFlow通過集中式的控制器將控制層面從傳統(tǒng)交換機(jī)中剝離,以下發(fā)流表的方式指揮交換機(jī)處理網(wǎng)絡(luò)流量,交換機(jī)只負(fù)責(zé)根據(jù)流表轉(zhuǎn)發(fā)。OpenFlow這種流表方式的管理使得網(wǎng)絡(luò)數(shù)據(jù)的處理層次扁平化,能滿足更細(xì)粒度的處理要求。 本文針對數(shù)據(jù)中心常見的胖樹網(wǎng)絡(luò)拓?fù)?在使用單跳貪婪選路的DLB負(fù)載均衡算法基礎(chǔ)上,提出了一種基于OpenFlow的改進(jìn)的GLB負(fù)載均衡算法,該算法預(yù)先計算出網(wǎng)絡(luò)中所有主機(jī)兩兩之間存在的所有路徑,每條路徑包括從源主機(jī)至目的主機(jī)所需經(jīng)過的所有鏈路,算法基于這條路徑上所有鏈路的當(dāng)前可用帶寬為每條路徑生成一個權(quán)重,用以衡量該路徑的均衡程度。當(dāng)網(wǎng)絡(luò)中有數(shù)據(jù)流需要進(jìn)行選路,算法根據(jù)源和目的主機(jī)找出所有可用路徑,選出權(quán)重最高即均衡程度最好的路徑作為算法輸出,避免了單跳貪婪選路可能獲取的局部最優(yōu)路徑。本文使用OpenFlow的方法,在OpenFlow控制器POX平臺上以模塊的形式實(shí)現(xiàn)了這兩種算法。然后在經(jīng)過自定義修改的Mininet仿真平臺上,通過搭建胖樹拓?fù)涞臄?shù)據(jù)中心網(wǎng)絡(luò)環(huán)境,采用隨機(jī)流量場景,經(jīng)過實(shí)驗得出數(shù)據(jù),根據(jù)平均帶寬利用率、平均報文傳輸時延和鏈路負(fù)載抖動等性能指標(biāo),分析驗證了本文所提出的GLB算法在負(fù)載均衡性能優(yōu)于DLB算法。
[Abstract]:With the rise of the concept of "cloud", cloud storage, cloud computing, cloud video, cloud security and other cloud services have become popular. And behind this cloud wave is a large data center set up by major cloud service providers, through thousands of servers forming clusters, matching corresponding storage systems, network interconnection devices, and so on. Use virtualization to make full use of computing, storage and network resources. Within such a large data center, it is possible at any time for each server instance to have a variety of different applications that inject traffic into the network, How to balance the huge internal load and make full use of network resources is an urgent problem to be solved. OpenFlow technology originated from a research project at Stanford University and gradually developed into the concept of SDN. OpenFlow has naturally become the most widely used network protocol in SDN. OpenFlow takes the control level off from the traditional switch through a centralized controller, and directs the switch to process network traffic in the following way. The switch is only responsible for the flow table management based on the flow table forwarding. OpenFlow makes the network data processing level flat and can meet the requirements of finer granularity processing. In this paper, an improved GLB load balancing algorithm based on OpenFlow is proposed based on the single-hop greedy routing DLB load balancing algorithm, which is based on the common fat-tree network topology in the data center. The algorithm calculates in advance all paths that exist between two hosts in the network, and each path includes all the links from the source host to the destination host. Based on the current available bandwidth of all links on this path, the algorithm generates a weight for each path to measure the equilibrium of the path. When there is a data flow in the network to be selected, the algorithm finds out all available paths according to the source and destination host, and selects the path with the highest weight, that is, the best balanced path, as the output of the algorithm. The local optimal path that can be obtained by greedy single hop routing is avoided. In this paper, we use the method of OpenFlow to implement these two algorithms in the form of modules on the POX platform of OpenFlow controller. Then, on the Mininet simulation platform which has been customized and modified, by setting up the data center network environment of the fat tree topology, adopting the random traffic scene, the data is obtained through the experiment, according to the average bandwidth utilization rate, The performance indexes such as average packet transmission delay and link load jitter are analyzed and verified that the proposed GLB algorithm is superior to the DLB algorithm in load balancing performance.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.04

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相關(guān)期刊論文 前2條

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本文編號：2121454