本文選題：軟件定義網(wǎng)絡(luò) + 內(nèi)容分發(fā)網(wǎng)絡(luò)　； 參考：《浙江大學(xué)》2017年碩士論文

【摘要】：近年來,信息技術(shù)迅猛發(fā)展,隨著各種智能終端、應(yīng)用的出現(xiàn)和寬帶用戶量的迅速增長,網(wǎng)絡(luò)流量呈爆炸式增長,人們對(duì)于高質(zhì)量的內(nèi)容資源的需求也日益增加,給網(wǎng)絡(luò)基礎(chǔ)設(shè)施帶來了巨大的壓力。內(nèi)容分發(fā)網(wǎng)絡(luò)(Content Delivery Network,CDN)是一種提供可靠、有效的內(nèi)容傳輸?shù)募夹g(shù)。但是,傳統(tǒng)的CDN無法獲取網(wǎng)絡(luò)全局信息,且依賴于DNS進(jìn)行請求重定向,從而導(dǎo)致缺乏對(duì)路徑和服務(wù)器選擇的動(dòng)態(tài)控制。軟件定義網(wǎng)絡(luò)(Software Defined Network,SDN)是一種新型的網(wǎng)絡(luò)技術(shù),它將控制面與數(shù)據(jù)面分離,從而提供靈活的集中式動(dòng)態(tài)管理。將SDN技術(shù)應(yīng)用于CDN網(wǎng)絡(luò)中,可以實(shí)時(shí)監(jiān)測網(wǎng)絡(luò)狀態(tài)信息,并及時(shí)作出決策,同時(shí),可以在更細(xì)的時(shí)間細(xì)粒度上對(duì)用戶請求進(jìn)行重定向。論文首先提出了一種基于智能SDN的CDN網(wǎng)絡(luò)架構(gòu)。智能SDN通過引入智能中心,有效解決了對(duì)SDN控制器的功能需求不斷增加、智能決策要求不斷提升和多域SDN控制器間信息共享和交互等問題。論文提出了基于模型預(yù)測控制(Model Predictive Control,MPC)的CDN用戶請求分配算法。主要根據(jù)用戶QoE相關(guān)的兩個(gè)核心參數(shù):響應(yīng)時(shí)間和用戶帶寬滿足度,來對(duì)候選服務(wù)器和路徑選擇進(jìn)行聯(lián)合優(yōu)化。仿真結(jié)果表明,該算法在響應(yīng)時(shí)間和帶寬滿足度方面都有明顯的性能提升。并發(fā)現(xiàn)可以通過調(diào)整權(quán)重參數(shù)來體現(xiàn)響應(yīng)時(shí)間和帶寬滿足度兩個(gè)參數(shù)的不同優(yōu)先級(jí),以滿足不同網(wǎng)絡(luò)應(yīng)用的需要。為了進(jìn)一步優(yōu)化性能,論文又提出了一種將神經(jīng)網(wǎng)絡(luò)和MPC相結(jié)合的CDN用戶請求分配算法。該算法首先基于神經(jīng)網(wǎng)絡(luò)對(duì)不同路徑進(jìn)行評(píng)分,并根據(jù)路徑評(píng)分進(jìn)行用戶請求分配。仿真結(jié)果表明,由于神經(jīng)網(wǎng)絡(luò)的非線性映射能力和自學(xué)習(xí)能力,算法的性能得到了進(jìn)一步的提升。
[Abstract]:In recent years, with the rapid development of information technology, with the emergence of a variety of intelligent terminals, applications and rapid growth of broadband users, network traffic is explosive growth, people's demand for high-quality content resources is also increasing day by day. Put a lot of pressure on the network infrastructure. Content delivery Network (CDN) is a technology that provides reliable and efficient content delivery. However, the traditional CDN can not obtain global network information and rely on DNS for request redirection, which leads to the lack of dynamic control over path and server selection. Software defined Network (SDN) is a new type of network technology, which separates the control surface from the data surface and provides flexible centralized dynamic management. The application of SDN technology in CDN network can monitor the network state information in real time and make the decision in time. At the same time, it can redirect the user's request in a finer time and fine granularity. Firstly, a CDN network architecture based on intelligent SDN is proposed. Intelligent SDN can effectively solve the problems such as increasing demand for SDN controller, increasing intelligent decision requirement and information sharing and interaction among multi-domain SDN controllers by introducing intelligent SDN center. This paper presents a CDN user request allocation algorithm based on Model Predictive Control (MPC). According to two core parameters related to user QoS: response time and bandwidth satisfaction, the candidate server and path selection are jointly optimized. Simulation results show that the performance of the algorithm is improved in response time and bandwidth satisfaction. It is also found that different priorities of response time and bandwidth adequacy can be reflected by adjusting the weight parameters to meet the needs of different network applications. In order to further optimize the performance, a CDN user request allocation algorithm combining neural network and MPC is proposed. The algorithm firstly scores different paths based on neural network and assigns user requests according to path score. Simulation results show that the performance of the algorithm is further improved because of the nonlinear mapping ability and self-learning ability of the neural network.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP393.0

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本文編號(hào)：2032979