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@Select Types{,
Journal = "Band-1",
Title= "Quantitative Analysis of the Effects of Different Carbon Tax Levels on Emissions and Costs of Data Centers",
Author= "Sascha Bosse, Abdulrahman Nahhas and Klaus Turowski
",
Doi= "https://doi.org/10.30844/wi_2020_m2-bosse",
Abstract= "Emissions of greenhouse gases (GHG) have to be reduced to limit the impacts of climate change. For that reason, the introduction of carbon taxes has been discussed or performed in many countries. Data centers are accounting for an increasing fraction of GHG emissions, so that carbon taxation may lead to reduced emissions. In this paper, the effect of different carbon tax levels is analyzed in experiments based on real-world workload from 20 data centers hosting enterprise systems. From the results, it can be concluded that optimization potential can be addressed with server consolidation, limiting the additional costs to be expected. Additionally, the used power mix and the depreciation period have a strong influence on the additional cost as well as the optimization potential regarding emissions.
",
Keywords= "Carbon tax, Data center management, Server consolidation, Greenhouse gas emissions",
}
Sascha Bosse, Abdulrahman Nahhas and Klaus Turowski: Quantitative Analysis of the Effects of Different Carbon Tax Levels on Emissions and Costs of Data Centers. Online: https://doi.org/10.30844/wi_2020_m2-bosse (Abgerufen 18.04.24)
Open Access
Abstract
Abstract
Emissions of greenhouse gases (GHG) have to be reduced to limit the impacts of climate change. For that reason, the introduction of carbon taxes has been discussed or performed in many countries. Data centers are accounting for an increasing fraction of GHG emissions, so that carbon taxation may lead to reduced emissions. In this paper, the effect of different carbon tax levels is analyzed in experiments based on real-world workload from 20 data centers hosting enterprise systems. From the results, it can be concluded that optimization potential can be addressed with server consolidation, limiting the additional costs to be expected. Additionally, the used power mix and the depreciation period have a strong influence on the additional cost as well as the optimization potential regarding emissions.
Keywords
Schlüsselwörter
Carbon tax, Data center management, Server consolidation, Greenhouse gas emissions
References
Referenzen
1. M. R. Allen, et al.: Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways – Technical Summary. Intergovernmental Panel on Climate Change (2018)
2. UN Framework Convention on Climate Change. United Nations, available at http://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf (2015) (Accessed:
29.11.2019)
3. Klimaschutzziele Deutschlands. Umweltbundesamt der Bundesrepublik Deutschland, available at https://www.umweltbundesamt.de/daten/klima/klimaschutzziele-deutschlands (2019) (Accessed: 29.11.2019)
4. Bertram, C., Luderer, G., Pietzcker, R.C., Schmid, E., Kriegler, E., Edenhofer, O.: Complementing carbon prices with technology policies to keep climate targets within reach. Nature Climate Change 5, 235–239 (2015)
5. Okubo, T., Cole, M.A., Elliott, R.J.R.: Environmental Outsourcing. Research Institute of Economy, Trade and Industry Discussion Paper Series (2010)
6. Fiscal Policies for Paris Climate Strategies – From Principle to Practice. International Monetary Fund (2019)
7. Gilbertson, T., Reyes, O., Lohmann, L.: Carbon trading: how it works and why it fails. Dag Hammarskjöld Foundation Uppsala (2009)
8. Stram, B.N.: A new strategic plan for a carbon tax. Energy Policy 73, 519–523 (2014)
9. Le Quéré, C., Andrew, R.M., Friedlingstein, P., others: Global carbon budget 2018. Earth System Science Data 10 (2018)
10. Ekins, P., Andersen, M.S., Vos, H.: Environmental taxes: Implementation and environmental effectiveness. Publications Office of the European Union (1996)
11. Group, W.B.: Carbon Pricing Watch 2019. World Bank Group, available at https://openknowledge.worldbank.org/handle/10986/31755 (2016) (Accessed:
29.11.2019)
12. Belkhir, L., Elmeligi, A.: Assessing ICT global emissions footprint: Trends to 2040 & recommendations. Journal of Cleaner Production 177, 448–463 (2018)
13. Kosharnaya, Y., Yanchenko, S., Kulikov, A.: Specifics of Data Mining Facilities as Energy Consumers. In: 2018 Dynamics of Systems, Mechanisms and Machines (Dynamics). 1–4. IEEE (2018)
14. Gartner: Worldwide IT Spending Forecast, available at https://www.gartner.com/en/newsroom/press-releases/2019-10-07-gartner-saysglobal- it-spending-to-grow-06-in-2019 (2019) (Accessed: 29.11.2019)
15. Lopez-Pires, F., Baran, B.: Virtual machine placement literature review. arXiv preprint arXiv:1506.01509. (2015)
16. Speitkamp, B., Bichler, M.: A Mathematical Programming Approach for Server Consolidation Problems in Virtualized Data Centers. IEEE Transactions on Services Computing 3, 266–278 (2010)
17. Rolia, J., Andrzejak, A., Arlitt, M.: Automating Enterprise Application Placement in Resource Utilities. In: Brunner, M. and Keller, A. (eds.) 14th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management (DSOM). 118–129. Springer (2003)
18. Splieth, M., Bosse, S., Schulz, C., Turowski, K.: Analyzing the Effects of Load Distribution Algorithms on Energy Consumption of Servers in Cloud Data Centers. In: Proceedings of the 12th International Conference on Wirtschaftsinformatik (WI) (2015)
19. Bruvoll, A., Larsen, B.M.: Greenhouse gas emissions in Norway: do carbon taxes work? Energy policy 32, 493–505 (2004)
20. Davis, L.W., Kilian, L.: Estimating the effect of a gasoline tax on carbon emissions. Journal of Applied Econometrics 26, 1187–1214 (2011)
21. Lin, B., Li, X.: The effect of carbon tax on per capita CO2 emissions. Energy policy 39, 5137–5146 (2011)
22. Zhou, S., Shi, M., Li, N., Yuan, Y.: Impacts of carbon tax policy on CO2 mitigation and economic growth in China. Advances in Climate Change Research 2, 124–133 (2011)
23. Martin, R., De Preux, L.B., Wagner, U.J.: The impact of a carbon tax on manufacturing: Evidence from microdata. Journal of Public Economics 117, 1– 14 (2014)
24. Zhao, Y.-H.: The study of effect of carbon tax on the international competitiveness of energy-intensive industries: an empirical analysis of OECD 21 countries, 1992-2008. Energy Procedia 5, 1291–1302 (2011)
25. Brännlund, R., Nordström, J.: Carbon tax simulations using a household demand model. European Economic Review 48, 211–233 (2004)
26. Garey, M., Johnson, D.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman, San Francisco (1979)
27. Varasteh, A., Goudarzi, M.: Server Consolidation Techniques in Virtualized Data Centers: A Survey. IEEE Systems Journal 11, 772–783 (2017)
28. Le, K., Bianchini, R., Zhang, J., Jaluria, Y., Meng, J., Nguyen, T.D.: Reducing electricity cost through virtual machine placement in high performance computing clouds. In: 2011 International Conference for High Performance Computing, Networking, Storage and Analysis. 22:1–22:12. ACM (2011)
29. International Organization for Standardization: ISO 14044: Environmental management – Life cycle assessment – Requirements and guidelines (2006)
30. Barroso, L.A., Clidaras, J., Hölzle, U.: The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines. Synthesis Lectures on Computer Architecture 8, 1–154 (2013)
31. Bouley, D.: Estimating a Data Center’s Electrical Carbon Footprint. APC by Schneider Electric (2010)
32. Weber, C.: Uncertainty and variability in carbon footprinting for electronics case study of an IBM rackmount server (2011)
33. Goudarzi, H., Ghasemazar, M., Pedram, M.: SLA-based optimization of power and migration cost in cloud computing. In: Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012). 172–179. IEEE Computer Society (2012)
34. Grinshpan, L.: Solving enterprise applications performance puzzles: queuing models to the rescue. John Wiley & Sons (2012)
35. Müller, H., Bosse, S., Turowski, K.: Optimizing server consolidation for enterprise application service providers. In: Proceedings of the 2016 Pacific Asia Conference on Information Systems (2016)
36. CO2-Bepreisung in Deutschland: Ein Überblick über Handlungsoptionen und ihre Vor- und Nachteile. Umweltbundesamt der Bundesrepublik Deutschland (2019)
37. Mi, H., Wang, H., Yin, G., Zhou, Y., Shi, D., Yuan, L.: Online Self- Reconfiguration with Performance Guarantee for Energy-Efficient Large-Scale Cloud Computing Data Centers. In: IEEE International Conference on Services Computing (SCC). 514–521. IEEE, Miami, FL, USA (2010)
38. Stillwell, M., Schanzenbach, D., Vivien, F., Casanova, H.: Resource Allocation Algorithms for Virtualized Service Hosting Platforms. Journal of Parallel and Distributed Computing 70, 962–974 (2010)
39. Wu, L., Garg, S.K., Buyya, R.: SLA-based resource allocation for software as a service provider (SaaS) in cloud computing environments. In: Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. 195–204. IEEE Computer Society (2011)
40. Xu, J., Fortes, J.A.B.: Multi-objective Virtual Machine Placement in Virtualized Data Center Environments. In: IEEE/ACM International Conferenc on Cyber, Physical and Social Computing (CPSCom). IEEE, Hangzhou, China (2010)