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  • The GreenStar Network (GSN) is a CANARIE funded project led by École de Technologie Supérieure (Synchromedia). The goal of the GSN project is to create technology and standards for reducing the carbon footprint of Information and Communication Technology (ICT). ICT is responsible for 2% of global CO2 emissions, due to high consumption of electricity produced from coal.

    This project is based around three fundamental components:

    GreenStar Network

    • Networking and computational infrastructure at geographically distributed facilities is unified via the CANARIE network.
    • Middleware is being developed to provide cloud services to applications and users.
    • A "Carbon Protocol" is being developed for the ICT industry, providing a quantified approach to CO2 emission reductions, based on the ISO14064 family of standards.

  • GreenStar allow data to be beamed across the network to wherever renewable energy from solar and wind sources is available.

    The following video illustrate this principle which we call ''Follow the wind/ Follow the sun''.

    Simulation of small size GSN-like network with SCL Controller

    More info: http://www.greenservices.info/
    Carbon optimization in a medium-size network by GA algorithm (Simulation)

    This video is part of the research performed by Synchromedia Lab, ETS, Montreal in the GSN project.

  • Protocol: “ICT Greenhouse Gas Reduction Project Protocol: Quantification and Reporting”




    Online documentation and calculators:


      • Generate reports on potentially verifiable emission reductions that can be registered, verified, serialized and brought to market
      • Generate reports suitable for use in Corporate Sustainability Reporting http://icttool.ghgregistries.ca/index.cfm



    Opensource: Free for download under Apache 2.0 license



CANARIE and GSN positioning: January 2012 to March 2012 2012-03-15 GSN team is performing intensive tests of the CANARIE network, GSN infrastructure and GSN middleware to identify their limitations. Live data collection can be visualized at: Experimental scenarios, tools and discussions will be updated


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