ew 15(4): e1

Research Article

A Unified Monitoring Framework for Energy Consumption and Network Traffic

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  • @ARTICLE{10.4108/icst.tridentcom.2015.259704,
        author={Florentin Clouet and Simon Delamare and Jean-Patrick Gelas and Laurent Lef\'{e}vre and Lucas Nussbaum and Cl\^{e}ment Parisot and Laurent Pouilloux and Fran\`{e}ois Rossigneux},
        title={A Unified Monitoring Framework for Energy Consumption and Network Traffic},
        journal={EAI Endorsed Transactions on Energy Web},
        keywords={experimentation, monitoring, measurement, energy consumption, network traffic},
  • Florentin Clouet
    Simon Delamare
    Jean-Patrick Gelas
    Laurent Lefèvre
    Lucas Nussbaum
    Clément Parisot
    Laurent Pouilloux
    François Rossigneux
    Year: 2015
    A Unified Monitoring Framework for Energy Consumption and Network Traffic
    DOI: 10.4108/icst.tridentcom.2015.259704
Florentin Clouet1, Simon Delamare2, Jean-Patrick Gelas3, Laurent Lefèvre1, Lucas Nussbaum4,*, Clément Parisot1, Laurent Pouilloux1, François Rossigneux1
  • 1: Inria
  • 2: CNRS
  • 3: Université Lyon 1
  • 4: Université de Lorraine
*Contact email: lucas.nussbaum@inria.fr


Providing experimenters with deep insight about the effects of their experiments is a central feature of testbeds. In this paper, we describe Kwapi, a framework designed in the context of the Grid'5000 testbed, that unifies measurements for both energy consumption and network traffic. Because all measurements are taken at the infrastructure level (using sensors in power and network equipment), using this framework has no dependencies on the experiments themselves. Initially designed for OpenStack infrastructures, the Kwapi framework allows monitoring and reporting of energy consumption of distributed platforms. In this article, we present the extension of Kwapi to network monitoring, and outline how we overcame several challenges: scaling to a testbed the size of Grid'5000 while still providing high-frequency measurements; providing long-term loss-less storage of measurements; handling operational issues when deploying such a tool on a real infrastructure.