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SDLoad: an extensible framework for SDN workload generation

Authors:

Nicolas Laurent,

Stefano Vissicchio,

Marco CaniniAuthors Info & Claims

HotSDN '14: Proceedings of the third workshop on Hot topics in software defined networking

Pages 215 - 216

https://doi.org/10.1145/2620728.2620771

Published: 22 August 2014 Publication History

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Abstract

We propose a unified approach for workload generation to ease evaluation and comparison of SDN control-plane proposals. Our approach is based on SDLoad, an extensible framework capable of generating custom workloads satisfying input constraints, along user-defined evaluation axes.

References

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M. Canini et al. Software Transactional Networking: Concurrent and Consistent Policy Composition. In HotSDN, 2013.

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A. Dixit et al. Towards an Elastic Distributed SDN Controller. In HotSDN, 2013.

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ON.LAB. ONOS: Open Network Operating System. In ONS, 2014.

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P. Perenší et al. ESPRES: Easy Scheduling and Prioritization for SDN. In ONS, 2014.

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T. Koponen et al. Onix: A distributed control platform for large-scale production networks. In OSDI, 2010.

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A. Tootoonchian et al. On Controller Performance in Software-defined Networks. In Hot-ICE, 2012.

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S. Vissicchio et al. Safe Update of Hybrid SDN Networks. Technical report, UCLouvain, 2013.

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Cited By

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A VSingh HM SG J(2021)RNN-LSTM Based Deep Learning Model for Tor Traffic ClassificationCyber-Physical Systems10.1080/23335777.2021.19242849:1(25-42)Online publication date: 24-May-2021
https://doi.org/10.1080/23335777.2021.1924284
Yang SShi HZhang H(2020)Dynamic Load Balancing of Multiple Controller based on Intelligent Collaboration in SDN2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL)10.1109/CVIDL51233.2020.00-72(354-359)Online publication date: Jul-2020
https://doi.org/10.1109/CVIDL51233.2020.00-72
Yu YLi XLeng XSong LBu KChen YYang JZhang LCheng KXiao X(2019)Fault Management in Software-Defined Networking: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2018.286892221:1(349-392)Online publication date: Sep-2020
https://doi.org/10.1109/COMST.2018.2868922
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Index Terms

SDLoad: an extensible framework for SDN workload generation
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies
2. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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Information & Contributors

Information

Published In

HotSDN '14: Proceedings of the third workshop on Hot topics in software defined networking

August 2014

252 pages

ISBN:9781450329897

DOI:10.1145/2620728

Program Chairs:
Aditya Akella
University of Wisconsin-Madison, USA
,
Albert Greenberg
Microsoft, USA

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 August 2014

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Author Tags

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Poster

Funding Sources

Communauté française de Belgique

Conference

SIGCOMM'14

Sponsor:

SIGCOMM

SIGCOMM'14: ACM SIGCOMM 2014 Conference

August 22, 2014

Illinois, Chicago, USA

Acceptance Rates

HotSDN '14 Paper Acceptance Rate 50 of 114 submissions, 44%;

Overall Acceptance Rate 88 of 198 submissions, 44%

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Cited By

View all

A VSingh HM SG J(2021)RNN-LSTM Based Deep Learning Model for Tor Traffic ClassificationCyber-Physical Systems10.1080/23335777.2021.19242849:1(25-42)Online publication date: 24-May-2021
https://doi.org/10.1080/23335777.2021.1924284
Yang SShi HZhang H(2020)Dynamic Load Balancing of Multiple Controller based on Intelligent Collaboration in SDN2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL)10.1109/CVIDL51233.2020.00-72(354-359)Online publication date: Jul-2020
https://doi.org/10.1109/CVIDL51233.2020.00-72
Yu YLi XLeng XSong LBu KChen YYang JZhang LCheng KXiao X(2019)Fault Management in Software-Defined Networking: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2018.286892221:1(349-392)Online publication date: Sep-2020
https://doi.org/10.1109/COMST.2018.2868922
Fernandes SFernandes S(2017)Internet Traffic ProfilingPerformance Evaluation for Network Services, Systems and Protocols10.1007/978-3-319-54521-9_4(113-152)Online publication date: 22-Mar-2017
https://doi.org/10.1007/978-3-319-54521-9_4
Sieber CBlenk ABasta AKellerer W(2016)hvbench: An open and scalable SDN network hypervisor benchmark2016 IEEE NetSoft Conference and Workshops (NetSoft)10.1109/NETSOFT.2016.7502475(403-406)Online publication date: Jun-2016
https://doi.org/10.1109/NETSOFT.2016.7502475
Sieber CBasta ABlenk AKellerer W(2016)Online resource mapping for SDN network hypervisors using machine learning2016 IEEE NetSoft Conference and Workshops (NetSoft)10.1109/NETSOFT.2016.7502447(78-82)Online publication date: Jun-2016
https://doi.org/10.1109/NETSOFT.2016.7502447
Kreutz DRamos FEsteves Verissimo PEsteve Rothenberg CAzodolmolky SUhlig S(2015)Software-Defined Networking: A Comprehensive SurveyProceedings of the IEEE10.1109/JPROC.2014.2371999103:1(14-76)Online publication date: Jan-2015
https://doi.org/10.1109/JPROC.2014.2371999

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