TY - GEN
T1 - Application of genetic algorithm to maximise clean energy usage for data centres
AU - Carroll, Raymond
AU - Balasubramaniam, Sasitharan
AU - Botvich, Dmitri
AU - Donnelly, William
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Energy Efficiency
KW - Genetic Algorithm
KW - Green Data Centres
UR - https://www.scopus.com/pages/publications/84869595648
U2 - 10.1007/978-3-642-32615-8_56
DO - 10.1007/978-3-642-32615-8_56
M3 - Conference contribution
AN - SCOPUS:84869595648
SN - 9783642326141
VL - 87 LNICST
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
SP - 565
EP - 580
BT - Bio-Inspired Models of Network, Information, and Computing Systems - 5th International ICST Conference, BIONETICS 2010, Revised Selected Papers
T2 - 5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems, BIONETICS 2010
Y2 - 1 December 2010 through 3 December 2010
ER -
