Dynamic heterogeneity-aware resource provisioning in the cloud

IEEE Transactions on Cloud Computing

Volumn 2, Issue 1, 2014, Pages 14-28

  Zhang, Qi ^a   Zhani, Mohamed Faten ^a   Boutaba, Raouf ^a   Hellerstein, Joseph L ^b  

^a UNIVERSITY OF WATERLOO   (Canada)

^b GOOGLE INC   (United States)

Author keywords

Cloud computing; Energy management; Workload characterization

Indexed keywords

CLOUD COMPUTING; COMPUTER AIDED SOFTWARE ENGINEERING; ENERGY CONSERVATION; ENERGY MANAGEMENT; ENERGY UTILIZATION; K-MEANS CLUSTERING; SCHEDULING;

DIVERSE APPLICATIONS; DYNAMIC HETEROGENEITY; PERFORMANCE REQUIREMENTS; PRODUCTION ENVIRONMENTS; REDUCING ENERGY CONSUMPTION; RESOURCE REQUIREMENTS; TOTAL ENERGY CONSUMPTION; WORKLOAD CHARACTERIZATION;

GREEN COMPUTING;

EID: 84923288244     PISSN: None     EISSN: 21687161     Source Type: Journal    
DOI: 10.1109/TCC.2014.2306427     Document Type: Article

References (29)

1. Amazon Elastic Computing Cloud, http://aws.amazon.com/ec2/, 2013.
2. Energy Star Computer Server Qualified Product List, energystar.gov/ia/products/prod-lists/enterprise-servers-prod-list.xls, 2014.
3. Eucalyptus community, http://open.eucalyptus.com/, 2014.
4. Googleclusterdata - traces of google workloads, http://code.google.com/p/googleclusterdata/, 2014.
5. Technology research - Gartner Inc, www.gartner.com, 2014.
6. U.S. Energy Information Adminstration, http://www.eia.gov/, 2014.
7. G. Ananthanarayanan, A. Ghodsi, S. Shenker, and I. Stoica, "Effective Straggler Mitigation: Attack of the Clones," Proc. 10th USENIX Conf. Networked Systems Design and Implementation (NSDI), 2013.
8. R. Boutaba, L. Cheng, and Q. Zhang, "On Cloud Computational Models and the Heterogeneity Challenge," J. Internet Services and Applications, vol. 3, pp. 77-86, 2012.
9. G.E.P. Box, G.M. Jenkins, and G.C. Reinsel, Time Series Analysis, Forecasting, and Control. Third ed., Prentice-Hall, 1994.
10. S. Boyd et al., Convex Optimization. Cambridge Univ. Press, 2004.
11. C. Chekuri and S. Khanna, "On Multi-Dimensional Packing Problems,"Proc. Symp. Discrete Algorithms, 1999.
12. Y. Chen, A. Das, W. Qin, A. Sivasubramaniam, Q. Wang, and N. Gautam, "Managing Server Energy and Operational Costs in Hosting Centers," ACM SIGMETRICS Performance Evaluation Rev., vol. 33, pp. 303-314, 2005.
13. Y. Chen et al., "Analysis and Lessons from a Publicly Available Google Cluster Trace," Technical Report UCB/EECS-2010-95, 2010.
14. J. Diaz et al., "A Guide to Concentration Bounds," Handbook on Randomized Computing. Springer, 2001.
15. A. Ghodsi, M. Zaharia, B. Hindman, A. Konwinski, S. Shenker, and I. Stoica, "Dominant Resource Fairness: Fair Allocation of Multiple Resource Types," Proc. Eighth USENIX Conf. Networked Systems Design and Implementation (USENIX NSDI), 2011.
16. D. Gross and C. Harris, Fundamentals of Queueing Theory, pp. 244-247, John Wiley & Sons, 1998.
17. G. Jung, M.A. Hiltunen, K.R. Joshi, R.D. Schlichting, and C. Pu, "Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures," Proc. IEEE 30th Int'l Conf. Distributed Computing Systems (ICDCS), 2010.
18. S. Lee, R. Panigrahy, V. Prabhakaran, V. Ramasubrahmanian, K. Talwar, L. Uyeda, and U. Wieder, "Validating Heuristics for Virtual Machines Consolidation," Microsoft Research, MSR-TR-2011-9, 2011.
19. M. Lin, A. Wierman, L. Andrew, and E. Thereska, "Dynamic Right-Sizing for Power-Proportional Data Centers," Proc. IEEE INFOCOM, 2011.
20. A.K. Mishra, J.L. Hellerstein, W. Cirne, and C.R. Das, "Towards Characterizing Cloud Backend Workloads: Insights from Google Compute Clusters," ACM SIGMETRICS Performance Evaluation Rev., vol. 37, pp. 34-41, Mar. 2010.
21. C.D. Patel and A.J. Shah1, "Cost Model for Planning, Development and Operation of a Data Center," Technical Report HPL-2005-107(R.1), HP Laboratories Palo Alto, 2005.
22. A. Qureshi, R. Weber, H. Balakrishnan, J. Guttag, and B. Maggs, "Cutting the Electric Bill for Internet-Scale Systems," Proc. ACM SIGCOMM, 2009.
23. C. Reiss, A. Tumanov, G. Ganger, R. Katz, and M. Kozuch, "Heterogeneity and Dynamicity of Clouds at Scale: Google Trace Analysis," Proc. ACM Symp. Cloud Computing, 2012.
24. S. Ren et al., "Provably-Efficient Job Scheduling for Energy and Fairness in Geographically Distributed Data Centers," Proc. IEEE 32nd Int'l Conf. Distributed Computing Systems (ICDCS), 2012.
25. B. Sharma, V. Chudnovsky, J.L. Hellerstein, R. Rifaat, and C.R. Das, "Modeling and Synthesizing Task Placement Constraints in Google Compute Clusters," Proc. Second ACM Symp. Cloud Computing (SOCC), 2011.
26. A. Verma et al., "Pmapper: Power and Migration Cost Aware Application Placement in Virtualized Systems," Proc. Ninth ACM/IFIP/USENIX Int'l Conf. Middleware (Middleware), 2008.
27. Q. Zhang, J. Hellerstein, and R. Boutaba, "Characterizing Task usage Shapes Google's Compute Clusters," Proc. LADIS Workshop Held in Conjunction with VLDB, 2011.
28. Q. Zhang, M.F. Zhani, R. Boutaba, and J.L. Hellerstein, "HARMONY: Dynamic Heterogeneity-Aware Resource Provisioning in the Cloud," Proc. IEEE Int'l Conf. Distributed Computing Systems (ICDCS), 2013.
29. Q. Zhang, M.F. Zhani, Q. Zhu, S. Zhang, R. Boutaba, and J.L. Hellerstein, "Dynamic Energy-Aware Capacity Provisioning for Cloud Computing Environments," Proc. ACM Int'l Conf. Autonomic Computing (ICAC), 2012.