Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers

Research Article

Application of Genetic Algorithm to Maximise Clean Energy Usage for Data Centres

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  • @INPROCEEDINGS{10.1007/978-3-642-32615-8_56,
        author={Raymond Carroll and Sasitharan Balasubramaniam and Dmitri Botvich and William Donnelly},
        title={Application of Genetic Algorithm to Maximise Clean Energy Usage for Data Centres},
        proceedings={Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers},
        proceedings_a={BIONETICS},
        year={2012},
        month={10},
        keywords={Green Data Centres Energy Efficiency Genetic Algorithm},
        doi={10.1007/978-3-642-32615-8_56}
    }
    
  • Raymond Carroll
    Sasitharan Balasubramaniam
    Dmitri Botvich
    William Donnelly
    Year: 2012
    Application of Genetic Algorithm to Maximise Clean Energy Usage for Data Centres
    BIONETICS
    Springer
    DOI: 10.1007/978-3-642-32615-8_56
Raymond Carroll1,*, Sasitharan Balasubramaniam1,*, Dmitri Botvich1,*, William Donnelly1,*
  • 1: TSSG
*Contact email: rcarroll@tssg.org, sasib@tssg.org, dbotvich@tssg.org, wdonnelly@tssg.org

Abstract

The communications industry is currently witnessing a continued increase in energy consumption, and this trend is predicted to increase even more in the coming years. This is largely driven by the popularity of the Internet, which continues to attract growing numbers of users who now rely on the Internet as part of their daily lives. A major factor behind this attraction is the multitude of services available on the Internet, ranging from web based services (e.g. facebook) to heavy power consuming services such as multimedia (e.g. youtube, IPTV). Therefore the data centres housing these services are seeing their energy consumption increase proportionally, now leading researchers to actively search for solutions to improve the energy efficiency of data centres. In this paper we propose a green data centre solution that makes data centres and services prioritise the usage of clean, renewable energy sources. The solution allows data centres to share information regarding renewable energy and cooling, in order to exploit variance between different countries energy and temperature profiles by moving services between data centres. We employ a genetic-algorithm to find the optimal placement of services on the data centres.