A decision framework for placement of applications in clouds that minimizes their carbon footprint
Tóm tắt
Cloud computing gives users much freedom on where they host their computation and storage. However the CO2 emission of a job depends on the location and the energy efficiency of the data centers where it is run. We developed a decision framework that determines to move computation with accompanying data from a local to a greener remote data center for lower CO2 emissions. The model underlying the framework accounts for the energy consumption at the local and remote sites, as well as of networks among them. We showed that the type of network connecting the two sites has a significant impact on the total CO2 emission. Furthermore, the task’s complexity is a factor in deciding when and where to move computation.
Tài liệu tham khảo
Stansberry M, Kundritzki J: Uptime institute 2012 data center industry survey. 2012.http://uptimeinstitute.com [online] . Accessed 13 Dec 2013
[online] .http://www.thegreenitreview.com/2013/05/european-data-centres-are-less-energy.html [online] . Accessed 13 Dec 2013
Brown DJ, Reams C: Toward energy-efficient computing. Commun ACM 2010, 53(3):50–58. 10.1145/1666420.1666438
Taal A, Grosso P, Bomhof F: Transporting bits or transporting energy: does it matter? 2013.http://www.surf.nl/en/knowledge-and-innovation/knowledge-base/2013/research-report-transporting-bits-or-transporting-energy-does-it-matter.html [online] . Accessed 13 Dec 2013
Taal A, Drupsteen D, Makkes M, Grosso P: Storage to Energy: modeling the carbon emission of storage task offloading between data centers. In IEEE Consumer Communications and Networking Conference (CCNC). Las Vegas: IEEE; 2014.
IEA: CO2 emissions from fuel combustion–highlights.. Paris; 2011. [online] .http://www.iea.org/co2highlights/co2highlights.pdf [online] . Accessed 13 Dec 2013
[online] .http://en.wikipedia.org/wiki/Emission_intensity [online] . Accessed 13 Dec 2013
Sovacool BK: Valuing the greenhouse gas emissions from nuclear power: a critical survey. Energy Policy 2008, 36(8):2950–2963. 10.1016/j.enpol.2008.04.017
[online] .http://ec.europa.eu/energy/energy_policy/doc/factsheets/mix/mix_nl_en.pdf [online] . Accessed 13 Dec 2013
[online] .http://ec.europa.eu/energy/energy_policy/doc/factsheets/mix/mix_de_en.pdf [online] . Accessed 13 Dec 2013
[online] .http://ec.europa.eu/energy/energy_policy/doc/factsheets/mix/mix_at_en.pdf [online] . Accessed 13 Dec 2013
Rogers O, Cliff D: Options, forwards and provision-point contracts in improving cloud infrastructure utilisation. J Cloud Comput 2012, 1: 1–22.
Qureshi A, Weber R, Balakrishnan H, Guttag J, Maggs B: Cutting the electric bill for internet-scale systems. ACM SIGCOMM Comput Commun Rev 2009, 39(4):123–134. 10.1145/1594977.1592584
Rao L, Liu X, Xie L, Liu W: Minimizing electricity cost: optimization of distributed internet data centers in a multi-electricity-market environment. In INFOCOM, 2010 Proceedings IEEE. San Diego: IEEE; 2010:1–9.
Kant K: Data center evolution: a tutorial on state of the art, issues, and challenges. Comput Netw 2009, 53(17):2939–2965. 10.1016/j.comnet.2009.10.004
Baliga J, Ayre R, Hinton K, Tucker RS: Green cloud computing: Balancing energy in processing, storage, and transport. Proc IEEE 2011, 99: 149–167.
Tucker RS: Optical Packet-Switched WDM Networks–A Cost and Energy Perspective. In Optical Fiber Communication Conference, Optical Society of America. San Diego: IEEE; 2008:243–252.
Baliga J, Ayre R, Hinton K, Tucker R: Energy consumption in wired and wireless access networks. Commun Mag IEEE 2011, 49(6):70–77.
A calculator for a road to cleaner computing [Online] .http://sne.science.uva.nl/bits2energy/index.html [Online] . Accessed 13 Dec 2013
[online] .http://www.surfnet.nl/en/Hybride_netwerk/SURFinternet/Pages/kaart.aspx#topologie [online] . Accessed 13 Dec 2013