skip to main content
10.1145/1159913.1159928acmconferencesArticle/Chapter ViewAbstractPublication PagescommConference Proceedingsconference-collections
Article
Free access

Realistic and responsive network traffic generation

Published: 11 August 2006 Publication History

Abstract

This paper presents Swing, a closed-loop, network-responsive traffic generator that accurately captures the packet interactions of a range of applications using a simple structural model. Starting from observed traffic at a single point in the network, Swing automatically extracts distributions for user, application, and network behavior. It then generates live traffic corresponding to the underlying models in a network emulation environment running commodity network protocol stacks. We find that the generated traces are statistically similar to the original traces. Further, to the best of our knowledge, we are the first to reproduce burstiness in traffic across a range of timescales using a model applicable to a variety of network settings. An initial sensitivity analysis reveals the importance of capturing and recreating user, application, and network characteristics to accurately reproduce such burstiness. Finally, we explore Swing's ability to vary user characteristics, application properties, and wide-area network conditions to project traffic characteristics into alternate scenarios.

References

[1]
ABRY, P., AND VEITCH, D. Wavelet analysis of long-range-dependent traffic. IEEE Transactions on Information Theory 44, 1 (1998), 2--15.
[2]
Auckland-VI trace archive, University of Auckland, New Zealand. http://pma.nlanr.net/Traces/long/auck6.html.
[3]
BARFORD, P., AND CROVELLA, M. Generating representative web workloads for network and server performance evaluation. In MMCS (1998), pp. 151--160.
[4]
BARFORD, P., AND CROVELLA, M. Critical path analysis of TCP transactions. In ACM SIGCOMM (2000).
[5]
BENKO, P., AND VERES, A. A passive method for estimating end-to-end tcp packet loss. In IEEE Globecom (2002).
[6]
CAIDA. http://www.caida.org.
[7]
CAO, J., CLEVELAND, W., GAO, Y., JEFFAY, K., SMITH, F. D., AND WEIGLE, M. Stochastic models for generating synthetic http source traffic. In IEEE INFOCOMM (2004).
[8]
CHAN LAN, K., AND HEIDEMANN, J. A tool for rapid model parameterization and its applications. In MoMeTools Workshop (2003).
[9]
CHENG, Y. -C., HOELZLE, U., CARDWELL, N., SAVAGE, S., AND VOELKER, G. M. Monkey see, monkey do: A tool for tcp tracing and replaying. In USENIX Technical Conference (2004).
[10]
DANZIG, P. B., AND JAMIN, S. tcplib: A library of TCP/IP traffic characteristics. USC Networking and Distributed Systems Laboratory TR CS-SYS-91-01 (October, 1991).
[11]
DOVROLIS, C., RAMANATHAN, P., AND MOORE, D. Packet dispersion techniques and capacity estimation. In IEEE/ACM Transactions in Networking, Dec (2004).
[12]
FELDMANN, A., GILBERT, A. C., HUANG, P., AND WILLINGER, W. Dynamics of IP traffic: A study of the role of variability and the impact of control. In ACM SIGCOMM (1999).
[13]
FLOYD, S., AND PAXSON, V. Difficulties in simulating the internet. In IEEE/ACM Transactions on Networking (2001).
[14]
GUMMADI, K. P., DUNN, R. J., SAROIU, S., GRIBBLE, S. D., LEVY, H. M., AND ZAHORJAN, J. Measurement, modeling, and analysis of a peer-to-peer file-sharing workload. In Symposium on Operating Sytems Principles (SOSP) (2003).
[15]
HARFOUSH, K., BESTAVROS, A., AND BYERS, J. Measuring bottleneck bandwidth of targeted path. In IEEE INFOCOM (2003).
[16]
HERNANDEZ-CAMPOS, F., SMITH, F. D., AND JEFFAY, K. Generating realistic tcp workloads. In CMG2004 Conference (2004).
[17]
HUANG, P., FELDMANN, A., AND WILLINGER, W. A non-intrusive, wavelet-based approach to detecting network performance problems. In Internet Measurement Workshop (2001).
[18]
JAIN, M., AND DOVROLIS, C. End-to-end available bandwidth: Measurement methodology, dynamics, and relation with tcp throughput. In ACM SIGCOMM (2002).
[19]
JAIN, M., AND DOVROLIS, C. Ten fallacies and pitfalls in end-to-end available bandwidth estimation. In Internet Measurement Conference (2004).
[20]
JAISWAL, S., IANNACONE, G., DIOT, C., KUROSE, J., AND TOWSLEY, D. Inferring tcp connection characteristics through passive measurements. In IEEE INFOCOM (2004).
[21]
JIANG, H., AND DOVROLIS, C. Why is the internet traffic bursty in short (sub-rtt) time scales? In SIGMETRICS (2005).
[22]
KARAGIANNIS, T., PAPAGIANNAKI, K., AND FALOUTSOS, M. Blinc: Multilevel traffic classification in the dark. In ACM SIGCOMM (2005).
[23]
LE, L., AIKAT, J., JEFFAY, K., AND SMITH, F. D. The Effects of Active Queue Management on Web Performance. In ACM SIGCOMM (2003).
[24]
LEE, B. O., FROST, V. S., AND JONKMAN, R. Netspec 3. 0 source models for telnet, ftp, voice, video and WWW traffic. In Technical Report ITTC-TR-10980-19, University of Kansas (1997).
[25]
MAH, B. A. An empirical model of HTTP network traffic. In IEEE INFOCOM (2) (1997).
[26]
Mawi working group traffic archive. http://tracer.csl.sony.co.jp/mawi/.
[27]
MEDINA, A., TAFT, N., SALAMATIAN, K., BHATTACHARYYA, S., AND DIOT, C. Traffic Matrix Estimation: Existing Techniques and New Directions. In ACM SIGCOMM (2002).
[28]
MOORE, A., AND ZUEV, D. Internet traffic classification using bayesian analysis techniques. In ACM SIGMETRICS (2005).
[29]
The national laboratory for applied network research (nlanr) http://www.nlanr.net.
[30]
The network simulator ns-2. http://www.isi.edu/nsnam/ns.
[31]
PAXSON, V. Empirically derived analytic models of wide-area TCP coections. IEEE/ACM Transactions on Networking 2, 4 (1994), 316--336.
[32]
PAXSON, V. End-to-end internet packet dynamics. In IEEE/ACM Transactions on Networking, Vol. 7, No. 3 (June, 1999), pp. 277--292.
[33]
RUPP, A., DREGER, H., FELDMANN, A., AND SOMMER, R. Packet trace manipulation framework for test labs. In Internet Measurement Conference (2004).
[34]
SEN, S., AND WANG, J. Analyzing peer-to-peer traffic across large networks. In ACM SIGCOMM Internet measurement workshop (2002).
[35]
SMITH, F. D., HERNANDEZ-CAMPOS, F., JEFFAY, K., AND OTT, D. What TCP/IP protocol headers can tell us about the web. In SIGMETRICS/Performance (2001), pp. 245--256.
[36]
SOMMERS, J., AND BARFORD, P. Self-configuring network traffic generation. In Internet Measurement Conference (2004).
[37]
STANIFORD, S., PAXSON, V., AND WEAVER, N. How to 0wn the Internet in Your Spare Time. In USENIX Security Symposium (2002).
[38]
TANG, W., FU, Y., CHERKASOVA, L., AND VAHDAT, A. Medisyn: a synthetic streaming media service workload generator. In 13th International workshop on NOSSDAV (2003).
[39]
VAHDAT, A., YOCUM, K., WALSH, K., MAHADEVAN, P., KOSTIC, D., CHASE, J., AND BECKER, D. Scalability and accuracy in a large-scale network emulator. In Operating Systems Design and Implementation (OSDI) (2002).
[40]
WHITE, B., LEPREAU, J., STOLLER, L., RICCI, R., GURUPRASAD, S., NEWBOLD, M., HIBLER, M., BARB, C., AND JOGLEKAR, A. An Integrated Experimental Environment for Distributed Systems and Networks. In Operating Sytems Design and Implementation (OSDI) (2002).
[41]
WILLINGER, W., PAXSON, V., AND TAQQU, M. S. Self-similarity and Heavy Tails: Structural Modeling of Network Traffic. In A Practical Guide to Heavy Tails: Statistical Techniques and Applications (1998).
[42]
XU, K., ZHANG, Z.-L., AND BHATTACHARYA, S. Profiling internet backbone traffic: Behavior models and applications. In ACM SIGCOMM (2005).
[43]
YOCUM, K., EADE, E., DEGESYS, J., BECKER, D., CHASE, J., AND VAHDAT, A. Toward scaling network emulation using topology partitioning. In Eleventh IEEE/ACM International Symposium on Modeling, Analysis, and Simulation of Computer and Telecounication Systems (MASCOTS) (2003).
[44]
ZHANG, Y., BRESLAU, L., PAXSON, V., AND SHENKER, S. Onthe characteristics and origins of internet flow rates. In ACM SIGCOMM (2002).
[45]
ZHANG, Y., PAXSON, V., AND SHENKER, S. The stationarity of internet path properties: Routing, loss, and throughput. ACIRI Technical Report (2000).

Cited By

View all
  • (2024)Regional Features Conditioned Diffusion Models for 5G Network Traffic GenerationProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691312(396-409)Online publication date: 29-Oct-2024
  • (2024)FLuMe: Understanding Differential Spectrum Mobility Features in High ResolutionIEEE Transactions on Mobile Computing10.1109/TMC.2024.344215123:12(14186-14200)Online publication date: Dec-2024
  • (2022)Requirements for Crafting Virtual Network Packet CapturesJournal of Cybersecurity and Privacy10.3390/jcp20300262:3(516-526)Online publication date: 6-Jul-2022
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
SIGCOMM '06: Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
September 2006
458 pages
ISBN:1595933085
DOI:10.1145/1159913
  • cover image ACM SIGCOMM Computer Communication Review
    ACM SIGCOMM Computer Communication Review  Volume 36, Issue 4
    Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
    October 2006
    445 pages
    ISSN:0146-4833
    DOI:10.1145/1151659
    Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 August 2006

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. burstiness
  2. energy plot
  3. generator
  4. internet
  5. modeling
  6. structural model
  7. traffic
  8. wavelets

Qualifiers

  • Article

Conference

SIGCOMM06
Sponsor:
SIGCOMM06: ACM SIGCOMM 2006 Conference
September 11 - 15, 2006
Pisa, Italy

Acceptance Rates

Overall Acceptance Rate 462 of 3,389 submissions, 14%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)177
  • Downloads (Last 6 weeks)11
Reflects downloads up to 09 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Regional Features Conditioned Diffusion Models for 5G Network Traffic GenerationProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691312(396-409)Online publication date: 29-Oct-2024
  • (2024)FLuMe: Understanding Differential Spectrum Mobility Features in High ResolutionIEEE Transactions on Mobile Computing10.1109/TMC.2024.344215123:12(14186-14200)Online publication date: Dec-2024
  • (2022)Requirements for Crafting Virtual Network Packet CapturesJournal of Cybersecurity and Privacy10.3390/jcp20300262:3(516-526)Online publication date: 6-Jul-2022
  • (2021)Encapcap: Transforming Network Traces to Virtual Networks2021 IEEE 7th International Conference on Network Softwarization (NetSoft)10.1109/NetSoft51509.2021.9492602(437-442)Online publication date: 28-Jun-2021
  • (2020)Comparison and Detection Analysis of Network Traffic Datasets Using K-Means Clustering AlgorithmJournal of Information & Knowledge Management10.1142/S021964922050026419:03(2050026)Online publication date: 3-Aug-2020
  • (2020)Towards Generating Benchmark Datasets for Worm Infection Studies2020 10th International Symposium onTelecommunications (IST)10.1109/IST50524.2020.9345845(1-8)Online publication date: 15-Dec-2020
  • (2019)DETERProceedings of the 16th USENIX Conference on Networked Systems Design and Implementation10.5555/3323234.3323270(437-451)Online publication date: 26-Feb-2019
  • (2019)BlinkProceedings of the 16th USENIX Conference on Networked Systems Design and Implementation10.5555/3323234.3323248(161-176)Online publication date: 26-Feb-2019
  • (2019)Mimicking Human Behavior in Shared-Resource Computer Networks2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI)10.1109/IRI.2019.00062(356-363)Online publication date: 30-Jul-2019
  • (2018)Large-Scale Realistic Network Data Generation on a Budget2018 IEEE International Conference on Information Reuse and Integration (IRI)10.1109/IRI.2018.00012(23-30)Online publication date: 6-Jul-2018
  • Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media