Cloud auto-scaling with deadline and budget constraints

Proceedings - IEEE/ACM International Workshop on Grid Computing

Volumn , Issue , 2010, Pages 41-48

  Mao, Ming ^a   Li, Jie ^a   Humphrey, Marty ^a  

^a University of Virginia   (United States)

Author keywords

Auto scaling; Cloud computing; Dynamic scalability; Integer programming

Indexed keywords

ACQUISITION TIME; AUTO-SCALING; BUDGET CONSTRAINT; COMPUTING PLATFORM; COMPUTING RESOURCE; DYNAMIC BEHAVIORS; ON-DEMAND COMPUTING; SCALE DOWN; SCALE-UP; SCALING MECHANISM; STORAGE CAPACITY; USER COST;

BUDGET CONTROL; COMPUTER SYSTEMS; DYNAMICS; GRID COMPUTING; INTEGER PROGRAMMING; SCALABILITY; WINDOWS OPERATING SYSTEM;

CLOUD COMPUTING;

EID: 79951587347     PISSN: 15505510     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GRID.2010.5697966     Document Type: Conference Paper

References (14)

1. AWS auto-scaling. http://aws.amazon.com/autoscaling/
2. Windows Azure. http://www.microsoft.com/windowsazure/
3. RightScale. http://www.rightscale.com
4. M. Assuncao et al., Evaluating the Cost-Benefit of Using Cloud Computing to Extend the Capacity of Clusters, 18th ACM International Symposium on High performance Distributed Computing (HPDC 2009), pp. 141-150.
5. Z. Hill, J. Li, M. Mao, A. Ruiz-Alvarez, and M. Humphrey, Early Observations on the Performance of Windows Azure, 1st workshop on Scientific Cloud Computing, 2010.
6. R. Doyle, J. Chase, O. Asad, W. Jin, and A. Vahdat, Model-Based Resource Provisioning in a Web Service Utility, in Proceedings of the USENIX Symposium on Internet Technologies and Systems, 2003.
7. J. Li, D. Agarwal, M. Humphrey, C. Ingen, K. Jackson, Y. Ryu, eScience in the Cloud: A MODIS Satellite Data Reprojection and Reduction Pipeline in Windows Azure Platform, IPDPS, 2010
8. Trieu C. Chieu, Ajay Mohindra, Alexei A. Karve, Alla Segal: Dynamic Scaling of Web Applications in a Virtualized Cloud Computing Environment. ICEBE 2009: 281-286
9. H. Lim, S. Babu, J. Chase, and S. Parekh. Automated Control in Cloud Computing: Challenges and Opportunities. In 1st Workshop on Automated Control for Datacenters and Clouds, June 2009.
10. P. Padala, K. Shin, X. Zhu, M. Uysal, Z. Wang, S. Singhal, A. Merchant, and K. Salem. Adaptive Control of Virtualized Resources in Utility Computing Environments. EuroSys, 2007
11. Microsoft Solver Foundation. http://code.msdn.microsoft.com/ solverfoundation
12. B. Urgaonkar, P. Shenoy, A. Chandra, and P. Goyal. Dynamic provisioning of multi-tier internet applications. ICAC, 2005.
13. B. Rountree, D. Lowenthal, S. Funk, V. Freeh, B. Supinski, and M. Schulz, Bounding energy consumption in large-scale mpi programs. SC 2007, November 10-16, 2007.
14. V Swaminathan. and K. Chakrabarty. Real-time task scheduling for energy-aware embedded systems. In IEEE Real-Time Systems Symposium, November 2000.