CHARACTERIZING INTERNET BACKBONE TRAFFIC FROM MACRO TO MICRO

被引:0
|
作者
Yang, Jie [1 ]
He, Yang [1 ]
Lin, Ping [1 ]
Cheng, Gang [2 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
[2] EMC, Berkeley Hts, NJ 07922 USA
关键词
Traffic Characterization; Internet; Measurement;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The continuous growth in both commercial and public network traffic with various quality-of-service (QoS) requirements is calling for better service than the Internet's best effort mechanism. One of the challenging issues is to predict the overall behavior of aggregate network traffic. While network traffic characterization has been studied extensively due to its importance in network scheduling and throughput, an accurate characterization of network traffic still remains elusive. In this paper, in addition to characterizing the aggregate network traffic, we classify the traffic into different categories, e.g., P2P, VOIP, and provide insight to each of them in terms of their traffic pattern and impact to the overall traffic. Our study verifies that like many works reported in literature, majority Internet backbone traffic is contributed by a small portion of users. A major contribution of this paper is that we found a linear equation which could be used to approximate the impact of each User to the overall traffic. Many new applications appear recently and become more and more popular as Internet evolves. We show that in current Internet backbone of China, 9 applications, which can be classified into three categories, web browsing, P2P service, and gaming, contribute 95 percent of the total traffic. It is also demonstrated the P2P applications are the dominant traffic contributor among the three categories.
引用
收藏
页码:139 / +
页数:2
相关论文
共 50 条
  • [21] On the micro-macro limit in traffic flow
    Colombo, R. M.
    Rossi, E.
    RENDICONTI DEL SEMINARIO MATEMATICO DELLA UNIVERSITA DI PADOVA, 2014, 131 : 217 - 235
  • [22] Large-scale measurement and modeling of backbone Internet traffic
    Roughan, M
    Gottlieb, J
    INTERNET PERFORMANCE AND CONTROL OF NETWORK SYSTEMS III, 2002, 4865 : 190 - 201
  • [23] Traffic measurement and analysis in an ATM-based internet backbone
    Kawahara, R
    Ishibashi, K
    Hirano, T
    Saito, H
    Ohara, H
    Satoh, D
    Asano, S
    Matsukata, J
    COMPUTER COMMUNICATIONS, 2001, 24 (15-16) : 1508 - 1524
  • [24] Small-time scaling behavior of Internet backbone traffic
    Ribeiro, VJ
    Zhang, ZL
    Moon, S
    Diot, C
    COMPUTER NETWORKS, 2005, 48 (03) : 315 - 334
  • [25] Heuristics to classify Internet backbone traffic based on connection patterns
    John, Wolfgang
    Tafvelin, Sven
    2008 THE INTERNATIONAL CONFERENCE ON INFORMATION NETWORKING, 2008, : 221 - 225
  • [26] Soft Computing Techniques for Internet Backbone Traffic Anomaly Detection
    Azzini, Antonia
    De Felice, Matteo
    Meloni, Sandro
    Tettamanzi, Andrea G. B.
    APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS, 2009, 5484 : 99 - +
  • [27] Traffic characterization of network attack flows on the Internet backbone links
    Jeon, YJ
    Roh, BH
    Yoo, SW
    Kim, JS
    IC'04: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTERNET COMPUTING, VOLS 1 AND 2, 2004, : 335 - 338
  • [28] Characterizing peer-to-peer traffic across Internet
    Zhang, YF
    Lei, LH
    Chen, CJ
    GRID AND COOPERATIVE COMPUTING, PT 1, 2004, 3032 : 388 - 395
  • [29] FROM MACRO TO MICRO
    Ramirez Hernandez, Luis Fernando
    EQUIDAD & DESARROLLO, 2006, (06) : 5 - 6
  • [30] Reconstruction of Mixed Traffic Systems at Micro and Macro Scales
    Wang, Yanbing
    Fernandez, Fernando Garcia
    Li, Zhixiong
    IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2025, 17 (01) : 97 - 99