Goiri, Inigo and Le, Kien and Beauchea, Ryan and Guitart, Jordi (2014): Matching Renewable Energy Supply and Demand in Green Datacenters.
Preview |
PDF
MPRA_paper_104507.pdf Download (416kB) | Preview |
Abstract
In this paper, we propose GreenSlot, a scheduler for parallel batch jobs in a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot predicts the amount of solar energy that will be available in the near future, and schedules the workload to maximize the green energy consumption while meeting the jobs’ deadlines. If grid energy must be used to avoid deadline violations, the scheduler selects times when it is cheap. Our results for both scientific computing workloads and data processing workloads demonstrate that GreenSlot can increase solar energy consumption by up to 117% and decrease energy cost by up to 39%, compared to conventional schedulers. Based on these positive results, we conclude that green datacenters and green-energy-aware scheduling can have a significant role in building a more sustainable IT ecosystem.
Item Type: | MPRA Paper |
---|---|
Original Title: | Matching Renewable Energy Supply and Demand in Green Datacenters |
Language: | English |
Keywords: | Green energy, energy-aware job scheduling, datacenters |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General |
Item ID: | 104507 |
Depositing User: | oct cos |
Date Deposited: | 07 Dec 2020 09:37 |
Last Modified: | 07 Dec 2020 09:37 |
References: | [1] J. Koomey, Growth in Data Center Electricity Use 2005 to 2010, analytic Press (2011). [2] J. Mankoff, R. Kravets, E. Blevis, Some Computer Science Issues in Creating a Sustainable World, Computer 41 (8). [3] EcobusinessLinks, Green Web Hosts, http://www.ecobusinesslinks.com/ green_webhosts/ (Retrieved in 2013). [4] Apple, Apple and the Environment, http://www.apple.com/environment/ renewable-energy/ (2013). [5] Data Center Knowledge, Data Centers Scale Up Their Solar Power, http://www.datacenterknowledge.com/archives/2012/05/14/ data-centers-scale-up-their-solarpower/ (2012). [6] US Department of Energy, 2010 Solar Technologies Market Report, Tech. rep. (2011). [7] DSIRE, Database of State Incentives for Renewables and Efficiency, http://www. dsireusa.org/. [8] UK Government, Carbon Reduction Commitment, http://www. carbonreductioncommitment.info/. [9] I. Goiri, W. Katsak, K. Le, T. D. Nguyen, R. Bianchini, Parasol and GreenSwitch: Managing Datacenters Powered by Renewable Energy, in: ASPLOS, 2013. [10] A. Jossen, J. Garche, D. Sauer, Operation Conditions of Batteries in PV Applications, Solar Energy 76 (6). [12] A. Yoo, M. Jette, M. Grondona, SLURM: Simple Linux Utility for Resource Management, in: JSSPP, 2003. [13] Apache Hadoop, http://hadoop.apache.org/. [14] M. Arlitt, C. Bash, Y. Blagodurov, S. Chen, T. Christian, D. Gmach, C. Hyser, N. Kumari, Z. Liu, M. Marwah, A. McReynolds, C. Patel, A. Shah, Z. Wang, R. Zhou, Towards the Design and Operation of Net-Zero Energy Data Centers, in: ITherm, 2012. [15] B. Aksanli, J. Venkatesh, L. Zhang, T. Rosing, Utilizing Green Energy Prediction to Schedule Mixed Batch and Service Jobs in Data Centers, in: HotPower, 2011. [16] I. Goiri, K. Le, T. Nguyen, J. Guitart, J. Torres, R. Bianchini, GreenHadoop: Leveraging Green Energy in Data-Processing Frameworks, in: Eurosys, 2012. [17] K. Kant, M. Murugan, D. H. C. Du, Willow: A Control System for Energy and Thermal Adaptive Computing, in: IPDPS, 2011. [18] A. Krioukov, S. Alspaugh, P. Mohan, S. Dawson-Haggerty, D. Culler, R. Katz, Design and Evaluation of an Energy Agile Computing Cluster, Tech. Rep. EECS-2012- 13, University of California at Berkeley (January 2012). [19] C. Li, A. Qouneh, T. Li, iSwitch: Coordinating and Optimizing Renewable Energy Powered Server Clusters, in: ISCA, 2012. [20] C. Stewart, K. Shen, Some Joules Are More Precious Than Others: Managing Renewable Energy in the Datacenter, in: HotPower, 2009. [21] A. Krioukov, C. Goebel, S. Alspaugh, Y. Chen, D. Culler, R. Katz, Integrating Renewable Energy Using Data Analytics Systems: Challenges and Opportunities, Bulletin of the IEEE Computer Society Technical Committee. [22] Z. Liu, Y. Chen, C. Bash, A. Wierman, D. Gmach, Z. Wang, M. Marwah, C. Hyser, Renewable and Cooling Aware Workload Management for Sustainable Data Centers, in: SIGMETRICS, 2012. [23] K. Le, R. Bianchini, M. Martonosi, T. D. Nguyen, Cost- And Energy-Aware Load Distribution Across Data Centers, in: HotPower, 2009. [24] K. Le, O. Bilgir, R. Bianchini, M. Martonosi, T. D. Nguyen, Capping the Brown Energy Consumption of Internet Services at Low Cost, in: IGCC, 2010. [25] K. Le, J. Zhang, J. Meng, Y. Jaluria, T. D. Nguyen, R. Bianchini, Reducing Electricity Cost Through Virtual Machine Placement in High Performance Computing Clouds, in: SC, 2011. [26] Z. Liu, M. Lin, A. Wierman, S. Low, L. Andrew, Greening Geographical Load Balancing, in: SIGMETRICS, 2011. [27] Y. Zhang, Y. Wang, X. Wang, GreenWare: Greening Cloud-Scale Data Centers to Maximize the Use of Renewable Energy, in: Middleware, 2011. [28] N. Deng, C. Stewart, D. Gmach, M. Arlitt, J. Kelley, Adaptive Green Hosting, in: ICAC, 2012 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/104507 |