【摘要】：軟件定義網(wǎng)絡(luò)(Software Defined Networking,簡稱SDN)作為一種新型網(wǎng)絡(luò)架構(gòu),彌補(bǔ)了傳統(tǒng)網(wǎng)絡(luò)的諸多缺陷,為網(wǎng)絡(luò)創(chuàng)新提供了更多的機(jī)會(huì)。由于組播業(yè)務(wù)在傳統(tǒng)網(wǎng)絡(luò)里已比較成熟,SDN在革新傳統(tǒng)網(wǎng)絡(luò)過程中也有必要實(shí)現(xiàn)組播業(yè)務(wù),以完善自身所能提供的網(wǎng)絡(luò)服務(wù)。所以,如何設(shè)計(jì)和實(shí)現(xiàn)SDN架構(gòu)下的組播服務(wù)成為了 SDN領(lǐng)域內(nèi)亟待解決的主要問題之一。組播路由問題是提供組播服務(wù)所要解決的關(guān)鍵問題。在網(wǎng)絡(luò)業(yè)務(wù)中,服務(wù)質(zhì)量(Quality of Service,簡稱QoS)體現(xiàn)了網(wǎng)絡(luò)服務(wù)所能滿足用戶需求的程度,通常網(wǎng)絡(luò)業(yè)務(wù)的QoS要求會(huì)通過若干網(wǎng)絡(luò)性質(zhì)(如帶寬、時(shí)延等)的閾值約束來體現(xiàn),如何求解滿足服務(wù)質(zhì)量要求的QoS組播路由問題已成為當(dāng)今學(xué)術(shù)界研究的前沿課題之一。目前人們多采用進(jìn)化算法來求解QoS組播路由問題,包括蟻群優(yōu)化(Ant Colony Optimization,簡稱ACO)算法。然而現(xiàn)有ACO算法存在著耗時(shí)過長、全局搜索能力不強(qiáng)等缺陷,為此本文提出了一種新型ACO算法來求解帶寬、時(shí)延約束組播路由問題,該算法采用新型螞蟻尋路規(guī)則和信息素更新策略,彌補(bǔ)了已有ACO算法耗時(shí)過長的缺點(diǎn),使其局部搜索能力和全局搜索能力有了較大提升。本文自主生成了若干組播請求場景,用于模擬帶寬、時(shí)延約束組播路由問題。組播請求場景的仿真實(shí)驗(yàn)表明,本文提出的新型ACO算法相較于已有ACO算法在算法運(yùn)行時(shí)間性能上優(yōu)勢明顯,求得問題解的質(zhì)量更佳。但是,新型ACO算法耗時(shí)仍然較長,而果蠅優(yōu)化(Fruit Fly Optimization,簡稱FFO)算法這種新興進(jìn)化算法具有參數(shù)少、實(shí)現(xiàn)簡單、運(yùn)行速度快等優(yōu)點(diǎn),正彌補(bǔ)了新型ACO算法的不足。本文首次將FFO算法應(yīng)用于求解帶寬、時(shí)延約束組播路由問題,采用了一種新型果蠅位置表述方式,以使算法能用于求解組播路由問題。算法采用了果蠅嗅覺隨機(jī)搜索和視覺定位的新策略,以提升算法求解能力。通過仿真實(shí)驗(yàn)表明,本文采用的FFO算法相較于多種目前主流進(jìn)化算法在算法運(yùn)行時(shí)間、收斂速度和求解質(zhì)量等性能指標(biāo)上均有較大優(yōu)勢,證明了本文FFO算法性能的優(yōu)越性。本文設(shè)計(jì)并實(shí)現(xiàn)了一套SDN網(wǎng)絡(luò)QoS組播服務(wù)系統(tǒng)。該系統(tǒng)應(yīng)用Mininet仿真工具、Ryu控制器和OpenFlow協(xié)議及技術(shù)標(biāo)準(zhǔn),構(gòu)建了組播組管理、拓?fù)涔芾�、環(huán)路控制、QoS組播路由、請求調(diào)度等5大系統(tǒng)模塊。系統(tǒng)實(shí)現(xiàn)了本文提出ACO算法和FFO算法,用于組播路由計(jì)算環(huán)節(jié)。仿真實(shí)驗(yàn)表明,本系統(tǒng)能在SDN網(wǎng)絡(luò)中提供較完整的組播服務(wù),對如何在SDN架構(gòu)下提供組播服務(wù)提供了一定的參考價(jià)值。
[Abstract]:As a new network architecture, Software defined Network (SDN) makes up for many defects of traditional network and provides more opportunities for network innovation. Since multicast services are mature in traditional networks, it is necessary for SDN to realize multicast services in the process of reforming traditional networks in order to perfect the network services that they can provide. Therefore, how to design and implement multicast services based on SDN has become one of the most important problems in SDN. Multicast routing is a key problem in providing multicast services. In network services, quality of Service (QoS) reflects the degree to which network services can meet the needs of users. Usually, the QoS requirements of network services are reflected by the threshold constraints of some network properties (such as bandwidth, delay, etc.). How to solve QoS multicast routing problem which meets QoS requirements has become one of the leading topics in academic research. At present, evolutionary algorithms are widely used to solve QoS multicast routing problems, including Ant colony optimization (ACO) algorithm. However, the existing ACO algorithms have some shortcomings, such as long time consuming and weak global search ability. Therefore, a new ACO algorithm is proposed to solve the bandwidth, delay constrained multicast routing problem. The algorithm adopts new ant routing rules and pheromone updating strategy, which makes up for the long time consuming of the existing ACO algorithm and improves its local search ability and global search ability. In this paper, several multicast request scenarios are generated independently to simulate bandwidth and delay constrained multicast routing problems. The simulation results of multicast request scene show that the proposed new ACO algorithm is superior to the existing ACO algorithm in the performance of the algorithm's running time, and the quality of the solution to the problem is better than that of the existing ACO algorithm. However, the new ACO algorithm still takes a long time. Fruit fly Optimization (FFO), a new evolutionary algorithm, has the advantages of less parameters, simpler implementation and faster running speed, which makes up for the shortcomings of the new ACO algorithm. In this paper, the FFO algorithm is first applied to solve the bandwidth, delay constrained multicast routing problem. A new Drosophila location representation method is used to solve the multicast routing problem. The algorithm adopts a new strategy of random search of Drosophila olfactory and visual location to improve the ability of the algorithm. The simulation results show that the proposed FFO algorithm is superior to other popular evolutionary algorithms in terms of performance indexes such as running time, convergence speed and solution quality, which proves the superiority of the FFO algorithm in this paper. This paper designs and implements a set of QoS multicast service system in SDN network. Based on Mininet simulation tool, Ryu controller, OpenFlow protocol and technical standard, five system modules, such as multicast group management, topology management, loop control, QoS multicast routing and request scheduling, are constructed. ACO algorithm and FFO algorithm are proposed in this paper, which can be used in multicast routing computation. The simulation results show that the system can provide a complete multicast service in SDN network, which provides a certain reference value for how to provide multicast services in SDN architecture.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP393.02

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 霍慧慧;李國勇;;基于自適應(yīng)果蠅算法的神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)訓(xùn)練[J];微電子學(xué)與計(jì)算機(jī);2016年01期

2 陳杰;張洪偉;;基于自適應(yīng)蟻群算法的QoS組播路由算法[J];計(jì)算機(jī)工程;2008年13期

，

本文編號(hào)：2121420