本文選題：SDN　切入點：負(fù)載均衡　出處：《大連海事大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著近年來互聯(lián)網(wǎng)飛速發(fā)展,網(wǎng)絡(luò)流量呈現(xiàn)爆發(fā)式增長,數(shù)據(jù)中心作為其重要基礎(chǔ)設(shè)施也面臨著諸多挑戰(zhàn)。軟件定義網(wǎng)絡(luò)(Software Defined Network,SDN)是對傳統(tǒng)網(wǎng)絡(luò)架構(gòu)的一項重大變革,其核心理念是將數(shù)據(jù)層面與控制層面分離。本課題主要對基于SDN的數(shù)據(jù)中心網(wǎng)絡(luò)多路徑負(fù)載均衡策略進行了研究。針對數(shù)據(jù)中心網(wǎng)絡(luò)流量集中的特點,利用SDN集中式控制和軟件可編程的優(yōu)勢,通過多路徑負(fù)載分擔(dān)的方法提高網(wǎng)絡(luò)鏈路利用率,減少擁塞。本文選擇Ryu控制器作為研究平臺,通過REST API在應(yīng)用層自定義5個模塊來實現(xiàn)多路徑負(fù)載均衡策略,各模塊分別為.全局拓?fù)涓兄K,網(wǎng)絡(luò)狀態(tài)測量模塊,k短路徑計算模塊,鏈路狀態(tài)評估模塊和擁塞處理與流表轉(zhuǎn)發(fā)模塊。Ryu控制器周期性地調(diào)用全局拓?fù)涓兄K和網(wǎng)絡(luò)狀態(tài)測量模塊,來獲取網(wǎng)絡(luò)全局拓?fù)洹�、時延等信息,以實現(xiàn)動態(tài)監(jiān)控。通過k短路徑計算模塊、鏈路狀態(tài)評估模塊、擁塞處理與流表轉(zhuǎn)發(fā)模塊來實現(xiàn)當(dāng)前流量負(fù)載合理分配的功能。Ryu控制器能夠通過周期性發(fā)送LLDP報文來獲取全局網(wǎng)絡(luò)拓?fù)湫畔?并且可以使用軟件方法防止網(wǎng)絡(luò)環(huán)路和實現(xiàn)MAC地址學(xué)習(xí),利用OpenFlow協(xié)議可以實時監(jiān)測網(wǎng)絡(luò)帶寬、時延等參數(shù)。本文選用Yen算法作為KSP算法計算出k條備選路徑,并建立路徑評估模型,評定各備選鏈路優(yōu)先級,選擇當(dāng)前優(yōu)先級最高的鏈路作為轉(zhuǎn)發(fā)路徑,并將對應(yīng)的流表項下發(fā)到OpenFlow交換機。周期性監(jiān)控鏈路擁塞情況,在當(dāng)前轉(zhuǎn)發(fā)路徑的帶寬利用率達到閾值時,選擇除當(dāng)前路徑以外的最優(yōu)路徑實現(xiàn)重路由。本文利用Mininet仿真平臺模擬數(shù)據(jù)中心網(wǎng)絡(luò)胖樹拓?fù)浣Y(jié)構(gòu),并在Ryu控制器上實現(xiàn)本課題多路徑負(fù)載均衡策略,使用Mininet自帶的Iperf打流工具模擬流量發(fā)生,進行兩組對比實驗。實驗結(jié)果表明:本文調(diào)度策略在提高網(wǎng)絡(luò)鏈路利用率,降低時延,減少擁塞等方面有較好的效果。
[Abstract]:With the rapid development of the Internet in recent years, network traffic is exploding, and data center is facing many challenges as its important infrastructure. The core idea is to separate the data level from the control level. This paper mainly studies the multi-path load balancing strategy of the data center network based on SDN, aiming at the characteristics of the data center network traffic concentration. Taking advantage of the advantages of SDN centralized control and software programming, the multipath load sharing method is used to improve the network link utilization rate and reduce congestion. In this paper, the Ryu controller is chosen as the research platform. The multipath load balancing strategy is implemented by using REST API to customize five modules in the application layer. The modules are. Global topology perception module, network state measurement module and short path calculation module. The link state evaluation module and the congestion processing and flow table forwarding module .Ryu controller periodically call the global topology sensing module and the network state measurement module to obtain network global topology, bandwidth, delay and other information. In order to realize dynamic monitoring. Through k short path calculation module, link state evaluation module, Congestion processing and flow table forwarding module to realize the function of reasonable distribution of current traffic load. Ryu controller can obtain global network topology information by sending LLDP packets periodically. The software method can be used to prevent the network loop and realize MAC address learning, and the network bandwidth and delay can be monitored in real time by using the OpenFlow protocol. In this paper, the Yen algorithm is chosen as the KSP algorithm to calculate k alternative paths. A path evaluation model is established to evaluate the priority of each alternative link, and the link with the highest priority is selected as the forwarding path. The corresponding flow table items are sent to the OpenFlow switch, and the link congestion is monitored periodically. When the bandwidth utilization of the current forwarding path reaches the threshold, the optimal path other than the current path is chosen to realize the rerouting. This paper simulates the fat tree topology of the data center network by using the Mininet simulation platform. The multipath load balancing strategy is implemented on the Ryu controller, and the traffic generation is simulated by using the Iperf routing tool of Mininet. The experimental results show that the scheduling strategy in this paper can improve the network link utilization ratio. It has good effect in reducing delay and congestion.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP308;TP393.0

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