EAI Endorsed Transactions on Self-Adaptive Systems 16(8): e5

Research Article

TADA: An Active Measurement Tool for Automatic Detection of AQM

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  • @ARTICLE{10.4108/eai.14-12-2015.2262684,
        author={Minoo Kargar Bideh and Andreas Petlund and Carsten Griwodz and Iffat Ahmed and Razieh behjati and Anna Brunstrom and Stefan Alfredsson},
        title={TADA: An Active Measurement Tool for Automatic Detection of AQM},
        journal={EAI Endorsed Transactions on Self-Adaptive Systems},
        volume={16},
        number={8},
        publisher={ACM},
        journal_a={SAS},
        year={2016},
        month={1},
        keywords={active network measurement tool, network drop scheme detection, active queue management, tail-drop},
        doi={10.4108/eai.14-12-2015.2262684}
    }
    
  • Minoo Kargar Bideh
    Andreas Petlund
    Carsten Griwodz
    Iffat Ahmed
    Razieh behjati
    Anna Brunstrom
    Stefan Alfredsson
    Year: 2016
    TADA: An Active Measurement Tool for Automatic Detection of AQM
    SAS
    EAI
    DOI: 10.4108/eai.14-12-2015.2262684
Minoo Kargar Bideh1,*, Andreas Petlund1, Carsten Griwodz1, Iffat Ahmed1, Razieh behjati1, Anna Brunstrom2, Stefan Alfredsson2
  • 1: Simula Research Laboratory, Norway
  • 2: Karlstad University, Sweden
*Contact email: kargar@simula.no

Abstract

The problem of overbuffering in today's Internet (termed as bufferbloat) has recently drawn a great amount of attention from the research community. This has led to the development of various active queue management (AQM) schemes. The last years have seen a lot of effort to show the benefits of AQMs over simple tail-drop queuing and to encourage deployment. Yet it is still unknown to what extent AQMs are deployed in the Internet. In this paper, we present an end-to-end active measurement method to detect AQMs on the path bottleneck. We have developed an active measurement tool, named , and evaluated our measurement methodology on a controlled experimental testbed. Experimental results show that the proposed approach provides the basis to identify whether an AQM is deployed on the bottleneck.