SLA-tree: A framework for efficiently supporting SLA-based decisions in cloud computing

ACM International Conference Proceeding Series

Volumn , Issue , 2011, Pages 129-140

  Chi, Yun ^a   Moon, Hyun Jin ^a   Hacigümüş, Hakan ^a   Tatemura, Junichi ^a  

^a NEC LABORATORIES AMERICA   (United States)

Author keywords

Capacity planning; Cloud computing; Dispatching; Scheduling; Service level agreement; SLA tree

Indexed keywords

CLOUD COMPUTING; DATABASE SYSTEMS; DECISION MAKING; FORESTRY; QUERY PROCESSING; SCHEDULING; TREES (MATHEMATICS);

CAPACITY PLANNING; CLOUD SERVICE PROVIDERS; CLOUD-COMPUTING; DECISIONS MAKINGS; DISPATCHING; QUERY RESPONSE TIME; SCHEDULING; SERVICE LEVEL AGREEMENT-TREE; SERVICELEVEL AGREEMENT (SLA);

PROFITABILITY;

EID: 79953901381     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1951365.1951383     Document Type: Conference Paper

References (21)

1. D. J. Abadi, S. R. Madden, and N. Hachem. Column-stores vs. row-stores: how different are they really? In SIGMOD, 2008.
2. D. G. Campbell, G. Kakivaya, and N. Ellis. Extreme scale with full sql language support in microsoft sql azure. In SIGMOD, 2010.
3. B. N. Chun and D. E. Culler. User-centric performance analysis of market-based cluster batch schedulers. In CCGRID, 2002.
4. G. R. Dattatreya. Performance Analysis of Queuing and Computer Networks. Chapman and Hall, 2008.
5. S. Elnaffar, P. Martin, and R. Horman. Automatically classifying database workloads. In CIKM, 2002.
6. D. Florescu and D. Kossmann. Rethinking cost and performance of database systems. SIGMOD Record, 38(1):43-48, 2009.
7. A. Ganapathi, H. Kuno, U. Dayal, J. L. Wiener, A. Fox, M. Jordan, and D. Patterson. Predicting multiple metrics for queries: Better decisions enabled by machine learning. In ICDE, 2009.
8. M. R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman & Co., New York, NY, USA, 1979.
9. C. Gupta, A. Mehta, S. Wang, and U. Dayal. Fair, effective, efficient and differentiated scheduling in an enterprise data warehouse. In EDBT, 2009.
10. J. R. Haritsa, M. J. Carey, and M. Livny. Value-based scheduling in real-time database systems. The VLDB Journal, 2(2), 1993.
11. D. E. Irwin, L. E. Grit, and J. S. Chase. Balancing risk and reward in a market-based task service. In HPDC, 2004.
12. X. Kang, H. Zhang, G. Jiang, H. Chen, X. Meng, and K. Yoshihira. Understanding internet video sharing site workload: a view from data center design. In WWW, 2008.
13. D. Kossmann, T. Kraska, and S. Loesing. An evaluation of alternative architectures for transaction processing in the cloud. In SIGMOD, 2010.
14. J. Leung, L. Kelly, and J. H. Anderson. Handbook of Scheduling: Algorithms, Models, and Performance Analysis. CRC Press, Inc., 2004.
15. J. Peha and F. Tobagi. Cost-based scheduling and dropping algorithms to support integrated services. IEEE Trans. on Comm., 44(2):192-202, 1996. (Pubitemid 126771120)
16. F. I. Popovici and J. Wilkes. Profitable services in an uncertain world. In ACM/IEEE SC, 2005.
17. B. Schroeder and M. Harchol-Balter. Evaluation of task assignment policies for supercomputing servers: The case for load unbalancing and fairness. Cluster Computing, 7(2):151-161, 2004.
18. M. A. Sharaf, P. K. Chrysanthis, A. Labrinidis, and K. Pruhs. Efficient scheduling of heterogeneous continuous queries. In VLDB, 2006.
19. N. Ye, E. S. Gel, X. Li, T. Farley, and Y.-C. Lai. Web server qos models: applying scheduling rules from production planning. Comput. Oper. Res., 32(5), 2005.
20. H. Zhang, G. Jiang, K. Yoshihira, H. Chen, and A. Saxena. Resilient workload manager: taming bursty workload of scaling internet applications. In ICAC, 2009.
21. L. Zhang and D. Ardagna. Sla based profit optimization in autonomic computing systems. In ICSOC, 2004.