• DocumentCode
    3681207
  • Title

    Event-Driven Application Brownout: Reconciling High Utilization and Low Tail Response Times

  • Author

    David Desmeurs;Cristian Klein;Alessandro Vittorio Papadopoulos;Johan Tordsson

  • Author_Institution
    Dept. of Comput. Sci., Umea Univ., Umea, Sweden
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    12
  • Abstract
    Data centers currently waste a lot of energy, due to lack of energy proportionality and low resource utilization, the latter currently being necessary to ensure application responsiveness. To address the second concern we propose a novel application-level technique that we call event-driven Brownout. For each request, i.e., in an event-driven manner, the application can execute some optional code that is not required for correct operation but desirable for user experience, and does so only if the number of pending client requests is below a given threshold. We propose several autonomic algorithms, based on control theory and machine learning, to automatically tune this threshold based on measured application 95th percentile response times. We evaluate our approach using the RUBiS benchmark which shows a 11-fold improvement in maintaining response-time close to a set-point at high utilization compared to competing approaches. Our contribution is opening the path to more energy efficient data-centers, by allowing applications to keep response times close to a set-point even at high resource utilization.
  • Keywords
    "Time factors","Training","Feedforward neural networks","Machine learning algorithms","Algorithm design and analysis","Hardware","Admission control"
  • Publisher
    ieee
  • Conference_Titel
    Cloud and Autonomic Computing (ICCAC), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICCAC.2015.25
  • Filename
    7312136