本文選題：互聯(lián)網(wǎng)流量　切入點：流量矩陣　出處：《華中科技大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著IP網(wǎng)絡(luò)的飛速發(fā)展和網(wǎng)絡(luò)應(yīng)用的日益豐富，運營商對于網(wǎng)絡(luò)流量的精細(xì)化管理的需求愈加迫切。一方面，需要處理大量的采自于現(xiàn)實網(wǎng)絡(luò)的流量數(shù)據(jù)，以獲知網(wǎng)絡(luò)鏈路的利用率等狀態(tài)信息；另一方面，也需要對網(wǎng)絡(luò)流量的增長趨勢進(jìn)行預(yù)測，以便提前展開網(wǎng)絡(luò)規(guī)劃等工作。為了應(yīng)對這些需求，本文設(shè)計了一套IP骨干網(wǎng)絡(luò)流量的分析預(yù)測工具。 該網(wǎng)絡(luò)流量分析預(yù)測工具由數(shù)據(jù)預(yù)處理、節(jié)點流量分析、流量矩陣分析、節(jié)點流量預(yù)測以及流量矩陣預(yù)測等五部分構(gòu)成。該工具以現(xiàn)網(wǎng)實際采集的流量矩陣數(shù)據(jù)為主要分析數(shù)據(jù)，SNMP測量節(jié)點流量為輔助分析數(shù)據(jù)。在節(jié)點流量分析部分，提供了流量分解、流量建模、流量對比以及網(wǎng)絡(luò)鏈路負(fù)載計算等功能；在節(jié)點流量預(yù)測部分，，提供了ARIMA預(yù)測、多元回歸預(yù)測等功能；在矩陣流量分析部分，提供了對流量矩陣關(guān)鍵元素、扇出項等進(jìn)行觀察和分析的功能；在矩陣流量預(yù)測部分，可以把節(jié)點流量的預(yù)測結(jié)果分?jǐn)偟礁髁飨蛏�，對�?jié)點出入流量、鏈路負(fù)載利用率以及流量流向分配比例等進(jìn)行可視化展示。 本文實現(xiàn)的流量分析預(yù)測工具，已通過某運營商提供的現(xiàn)網(wǎng)實際采集流量數(shù)據(jù)的測試�？芍С謱嶋H流量數(shù)據(jù)的導(dǎo)入，可對網(wǎng)絡(luò)局部或者整體進(jìn)行分析與預(yù)測，并輸出圖形化報表。該工具能對網(wǎng)絡(luò)維護(hù)、網(wǎng)絡(luò)規(guī)劃提供科學(xué)的參考，起到積極有益的作用。
[Abstract]:With the rapid development of IP network and the increasingly rich network applications, the operators need to manage network traffic more and more urgently. On the one hand, a large number of traffic data collected from real networks need to be processed. In order to obtain status information such as the utilization rate of network links; on the other hand, it is also necessary to predict the growth trend of network traffic in order to carry out work such as network planning ahead of time. This paper designs a set of IP backbone network traffic analysis and prediction tools. The network traffic analysis and prediction tool consists of data preprocessing, node traffic analysis, traffic matrix analysis, The tool is composed of five parts: node flow prediction and traffic matrix prediction. This tool mainly analyzes the traffic matrix data collected by the network, and the SNMP traffic measurement node traffic is used as the auxiliary analysis data. In the node flow analysis part, The functions of traffic decomposition, traffic modeling, traffic comparison and network link load calculation are provided. In the node traffic prediction section, the functions of ARIMA prediction, multiple regression prediction, and matrix traffic analysis are provided. It provides the function of observing and analyzing the key elements of the flow matrix, fan out items, etc. In the forecasting part of the flow of the matrix, the forecast results of node flow can be apportioned to each flow direction, and the node flow in and out can be divided into and out. Link load utilization and flow flow distribution ratio are visualized. The traffic analysis and prediction tool realized in this paper has been tested by the actual traffic data collected by a network provided by a certain operator. It can support the introduction of actual traffic data and can be used to analyze and forecast the local or whole network. The tool can provide a scientific reference for network maintenance and network planning and play a positive and beneficial role.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.06

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本文編號：1559628