The Community for Technology Leaders
RSS Icon
Issue No.06 - Nov.-Dec. (2012 vol.16)
pp: 51-59
Reducing greenhouse gas (GHG) emissions is one of the most challenging research topics in ICT because of people's overwhelming use of electronic devices. Current solutions focus mainly on efficient power consumption at the micro level; few consider large-scale energy-management strategies. The low-carbon, nationwide GreenStar Network in Canada uses network and server virtualization techniques to migrate data center services among network nodes according to renewable energy availability. The network deploys a "follow the sun, follow the wind" optimization policy as a virtual infrastructure-management technique.
virtualisation, cloud computing, environmental factors, optimisation, virtual infrastructure-management technique, zero-carbon network, cloud computing, network virtualization, greenhouse gas emission, GHG emission, ICT, electronic device, power consumption, large-scale energy-management, GreenStar network, server virtualization technique, data center service, renewable energy, optimization policy, Green products, Renewable energy resources, Energy efficiency, Carbon dioxide, Servers, Computer architecture, Cloud computing, Virtual environments, cloud computing, Green products, Renewable energy resources, Energy efficiency, Carbon dioxide, Servers, Computer architecture, Cloud computing, Virtual environments, network virtualization, GreenStar Network, zero-carbon network, green ICT
M. Lemay, Kim-Khoa Nguyen, Bill St. Arnaud, M. Cheriet, "Toward a Zero-Carbon Network: Converging Cloud Computing and Network Virtualization", IEEE Internet Computing, vol.16, no. 6, pp. 51-59, Nov.-Dec. 2012, doi:10.1109/MIC.2011.128
1. P. Kurp, “Green Computing: Are You Ready for a Personal Energy Meter?” Comm. ACM, vol. 51, no. 10, 2008, pp. 11–13.
2. SMART2020: Enabling the Low Carbon Economy in the Information Age, tech. report, The Climate Group, 2008.
3. H.D. Saunders, The Khazzoom-Brookes Postulate and Neoclassical Growth, The Energy J., vol. 13, no. 4, 1992, pp. 131–148.
4. A. Qureshi et al., “Cutting the Electric Bill for Internet-Scale Systems,” ACM Computer Communication Rev., vol. 39, no. 4, 2009, pp. 123–134.
5. S. Figuerola et al., “Converged Optical Network Infrastructures in Support of Future Internet and Grid Services Using IaaS to Reduce GHG Emissions,” J. Lightwave Technology, vol. 27, no. 12, 2009, 1946, pp. 1941–1946.
6. V. Valancius et al., “Greening the Internet with Nano Data Centers,” Proc. 5th Int'l Conf. Emerging Networking Experiments and Technologies (CoNEXT 09), ACM, 2009, pp. 37–48.
7. K. Church et al., “On Delivering Embarrassingly Distributed Cloud Services,” Proc. Workshop Hot Topics in Networks (HotNets VII), ACM, 2008, pp. 55–60.
8. M. Lemay, “An Introduction to IaaS Framework,” workshop presentation, Inocybe Technologies, 5 Aug. 2008; .
9. C. Kiddle, “GeoChronos: A Platform for Earth Observation Scientists,” Open Grid Forum, 28 Mar. 2010; .
10. S. Figuerola and M. Lemay, “Infrastructure Services for Optical Networks,” J. Optical Communications and Networking, vol. 1, no. 2, 2009, pp. A247–A257.
11. J. Wu et al., “Layer 1 Virtual Private Network Management by Users,” Communications Magazine, vol. 44, no. 12, 2006, pp. 86–93.
12. E. Grasa et al., “The MANTICORE Project: Providing Users with a Logical IP Network Service,” Proc. TERENA Networking Conf., Trans-European Research and Education Networking Assoc., 2008; .
13. J. Baliga et al., “Energy Consumption in Optical IP Networks,” J. Lightwave Technology, vol. 27, no. 13, 2009, pp. 2391–2403.
260 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool