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Automating performance and energy consumption analysis for cloud applications

Authors

Fei Fei Chen, John Grundy, Jean-Guy Schneider, Yun Yang and Qiang He

Swinburne University of Technology

NICTA

Abstract

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed StressCloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. StressCloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of StressCloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.

BibTeX Entry

  @inproceedings{Chen_GSYH_15,
    publisher        = {IEEE},
    author           = {Chen, Fei Fei and Grundy, John and Schneider, Jean-Guy and Yang, Yun and He, Qiang},
    month            = may,
    year             = {2015},
    keywords         = {cloud computing, green computing, performance analysis, form chart, load test},
    title            = {Automating Performance and Energy Consumption Analysis for Cloud Applications},
    booktitle        = {IEEE SERVICES 2015 Visionary Track: The Future of Software Engineering FOR and IN Cloud},
    pages            = {8},
    address          = {New York, USA}
  }

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