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Packetlab: a universal measurement endpoint interface

Authors:

Kirill Levchenko,

Amogh Dhamdhere,

Bradley Huffaker,

Vern PaxsonAuthors Info & Claims

IMC '17: Proceedings of the 2017 Internet Measurement Conference

Pages 254 - 260

https://doi.org/10.1145/3131365.3131396

Published: 01 November 2017 Publication History

Abstract

The right vantage point is critical to the success of any active measurement. However, most research groups cannot afford to design, deploy, and maintain their own network of measurement endpoints, and thus rely measurement infrastructure shared by others. Unfortunately, the mechanism by which we share access to measurement endpoints today is not frictionless; indeed, issues of compatibility, trust, and a lack of incentives get in the way of efficiently sharing measurement infrastructure.

We propose PacketLab, a universal measurement endpoint interface that lowers the barriers faced by experimenters and measurement endpoint operators. PacketLab is built on two key ideas: It moves the measurement logic out of the endpoint to a separate experiment control server, making each endpoint a lightweight packet source/sink. At the same time, it provides a way to delegate access to measurement endpoints while retaining fine-grained control over how one's endpoints are used by others, allowing research groups to share measurement infrastructure with each other with little overhead. By making the endpoint interface simple, we also make it easier to deploy measurement endpoints on any device anywhere, for any period of time the owner chooses. We offer PacketLab as a candidate measurement interface that can accommodate the research community's demand for future global-scale Internet measurement.

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Cited By

Yan TZhang ZHuffaker BMok Rclaffy kLevchenko KMontpetit MLeivadeas AUhlig SJaved M(2023)Poster: Empirically Testing the PacketLab ModelProceedings of the 2023 ACM on Internet Measurement Conference10.1145/3618257.3624999(724-725)Online publication date: 24-Oct-2023
https://dl.acm.org/doi/10.1145/3618257.3624999
Luo ZLiu JYang GZhang YHang Z(2022)High-Speed Path Probing Method for Large-Scale NetworkSensors10.3390/s2215565022:15(5650)Online publication date: 28-Jul-2022
https://doi.org/10.3390/s22155650
Yan TChen YChen AZhang ZHuffaker BMok RLevchenko Kclaffy kBarakat CPelsser CBenson TChoffnes D(2022)PacketLabProceedings of the 22nd ACM Internet Measurement Conference10.1145/3517745.3563029(766-767)Online publication date: 25-Oct-2022
https://dl.acm.org/doi/10.1145/3517745.3563029
Show More Cited By

Index Terms

Packetlab: a universal measurement endpoint interface
1. Networks
  1. Network performance evaluation
    1. Network measurement

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cover image ACM Conferences

IMC '17: Proceedings of the 2017 Internet Measurement Conference

November 2017

509 pages

ISBN:9781450351188

DOI:10.1145/3131365

General Chairs:
Steve Uhlig
Queen Mary University of London
,
Olaf Maennel
Tallinn University of Technology

Copyright © 2017 ACM.

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 the author(s) 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].

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Published: 01 November 2017

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November 1 - 3, 2017

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Overall Acceptance Rate 277 of 1,083 submissions, 26%

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Cited By

Yan TZhang ZHuffaker BMok Rclaffy kLevchenko KMontpetit MLeivadeas AUhlig SJaved M(2023)Poster: Empirically Testing the PacketLab ModelProceedings of the 2023 ACM on Internet Measurement Conference10.1145/3618257.3624999(724-725)Online publication date: 24-Oct-2023
https://dl.acm.org/doi/10.1145/3618257.3624999
Luo ZLiu JYang GZhang YHang Z(2022)High-Speed Path Probing Method for Large-Scale NetworkSensors10.3390/s2215565022:15(5650)Online publication date: 28-Jul-2022
https://doi.org/10.3390/s22155650
Yan TChen YChen AZhang ZHuffaker BMok RLevchenko Kclaffy kBarakat CPelsser CBenson TChoffnes D(2022)PacketLabProceedings of the 22nd ACM Internet Measurement Conference10.1145/3517745.3563029(766-767)Online publication date: 25-Oct-2022
https://dl.acm.org/doi/10.1145/3517745.3563029
Jueckstock JSarker SSnyder PBeggs APapadopoulos PVarvello MLivshits BKapravelos A(2021)Towards Realistic and ReproducibleWeb Crawl MeasurementsProceedings of the Web Conference 202110.1145/3442381.3450050(80-91)Online publication date: 19-Apr-2021
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Roquero PMagaña ELeira RAracil J(2020)Performance evaluation of client-based traffic sniffing for very large populationsComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2019.106985166:COnline publication date: 15-Jan-2020
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Li MZong BLumezanu CChen H(2019)Learning IP network representationsACM SIGCOMM Computer Communication Review10.1145/3310165.331017248:5(48-54)Online publication date: 28-Jan-2019
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Li MLumezanu CZong BChen H(2018)Deep Learning IP Network RepresentationsProceedings of the 2018 Workshop on Big Data Analytics and Machine Learning for Data Communication Networks10.1145/3229607.3229609(33-39)Online publication date: 7-Aug-2018
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Sun WJiang JSu M(2018)A Passive-Measurement-Guided Tree Network Surveying and Mapping Model2018 IEEE Third International Conference on Data Science in Cyberspace (DSC)10.1109/DSC.2018.00103(646-651)Online publication date: Jun-2018
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