| 基于流的网络流量特征分析 |
| |
| 引用本文： | 马维旻,李忠诚.基于流的网络流量特征分析[J].小型微型计算机系统,2005,26(9):1454-1458. |
| |
| 作者姓名： | 马维旻 李忠诚 |
| |
| 作者单位： | 1. 北京师范大学,珠海分校信息技术学院,广东,珠海,519085
2. 中国科学院,计算技术研究所,信息网络室,北京,100080 |
| |
| 基金项目： | 国家“八六三”高技术研究发展计划项目基金（2002AA121032）资助. |
| |
| 摘 要： | 网络流量特征分析是提高网络性能的基础．其自相似特征是一个普遍存在的现象．通过对主干链路上的流量进行基于流的流量特征的分析，结果表明流间隔时间序列在小时间尺度上的自相似程度较弱，而大时间尺度上的自相似程度较强．进一步的分析表明，流的大小以及ICMP流对流的自相似特征有显著的影响，特别是流大小为1个包的流对其影响更大．
|
| 关 键 词： | 网络流量 特征 自相似 多分形 |
| 文章编号： | 1000-1220（2005）09-1454-05 |
| 收稿时间： | 2004-02-27 |
| 修稿时间： | 2004-02-27 |
Analysis of Network Traffic Based on Flow Level |
| |
| MA Wei-min,LI Zhong-cheng.Analysis of Network Traffic Based on Flow Level[J].Mini-micro Systems,2005,26(9):1454-1458. |
| |
| Authors: | MA Wei-min LI Zhong-cheng |
| |
| Abstract: | The analyzing characteristic of network traffic is the base to prompt network performance. The self-similarity is a common characteristic of network traffic. Through the analyzing characteristics of backbone network traffic at flow level, it shows that the self-similarity of the time series of flow intervals at small time scales is weaker whereas it is stronger at large time scales. The further study shows the size of flows and the ICMP flows apparently affects the self-similarity. Especially, those flows of one packet have larger effects. |
| |
| Keywords: | network traffic characteristics self-similar multi-fractal |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
