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GreenLight Data Collection Architecture

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Data collection architecture overview by Ingolf Krueger, Claudiu Farcas, 2010

Data collection architecture overview by Ingolf Krueger, Claudiu Farcas, 2010

Published in: Technology
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  • 1. Data Collection meeting Claudiu Farcas, Filippo Seracini, Ingolf Krueger
  • 2. Our objectives
    • Create an energy model for the BlackBox
      • Understand energy consumption related to task execution
      • Optimize task scheduling to decrease the environmental impact
      • Provide to user different modes of computation (i.e. max performance, max energy saving, min computational cost, etc)
    • Create the cyberinfrastructure to
      • Manage and control the Blackbox
      • Run tasks
      • Provide green data related to task execution
  • 3. First steps
    • Requirement engineering with the different teams involved in the project
      • What are the data sources?
      • What can be measured?
      • How is data stored?
      • How is data represented?
      • Who wants what?
  • 4. Research Distribution
    • GreenLight Researchers are interested in both producing and consuming greening data such as temperature and power measurements
  • 5. Existing Capabilities
    • Default Sun Monitoring interface
  • 6. Initial Domain Models
    • Data Collection Points
  • 7. Resource Allocation
    • Requirements elicitation at the 2 nd meeting
  • 8. Next Steps
    • Define a model for “greening data”
    • Define a resource model for GreenLight resources (e.g., CPUs, VMs, nodes, etc)
    • Model GreenLight resources in the context of the Rich Services framework (SOA derivate)
    • Identify usage policies and adequate scheduling algorithms to improve efficiency
    • Create the Rich Service infrastructure to use and manage the Blackbox
    • Expose the “green data” as web services & portal

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