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Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters
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High Performance Distributed Computing archive
Proceedings of the 18th ACM international symposium on High performance distributed computing table of contents
Garching, Germany
SESSION: Resource management and scheduling table of contents
Pages 141-150  
Year of Publication: 2009
ISBN:978-1-60558-587-1
Authors
Marcos Dias de Assuncao  The University of Melbourne, Melbourne, Australia
Alexandre di Costanzo  The University of Melbourne, Melbourne, Australia
Rajkumar Buyya  The University of Melbourne, Melbourne, Australia
Sponsors
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we investigate the benefits that organisations can reap by using "Cloud Computing" providers to augment the computing capacity of their local infrastructure. We evaluate the cost of six scheduling strategies used by an organisation that operates a cluster managed by virtual machine technology and seeks to utilise resources from a remote Infrastructure as a Service (IaaS) provider to reduce the response time of its user requests. Requests for virtual machines are submitted to the organisation's cluster, but additional virtual machines are instantiated in the remote provider and added to the local cluster when there are insufficient resources to serve the users' requests. Naïve scheduling strategies can have a great impact on the amount paid by the organisation for using the remote resources, potentially increasing the overall cost with the use of IaaS. Therefore, in this work we investigate six scheduling strategies that consider the use of resources from the "Cloud", to understand how these strategies achieve a balance between performance and usage cost, and how much they improve the requests' response times.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Amazon Inc. Amazon Elastic Compute Cloud (Amazon EC2). http://aws.amazon.com/ec2.
 
2
M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, G. Lee, D. A. Patterson, A. Rabkin, I. Stoica, and M. Zaharia. Above the clouds: A Berkeley view of Cloud computing. Technical report UCB/EECS-2009-28, Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, USA, February 2009.
 
3
4
 
5
R. Buyya and M. Murshed. GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing. Concurrency and Computation: Practice and Experience (CPE), 14(13-15):1175--1220, November-December 2002.
 
6
 
7
 
8
 
9
 
10
W. Emeneker, D. Jackson, J. Butikofer, and D. Stanzione. Dynamic virtual clustering with Xen and Moab. In Frontiers of High Performance Computing and Networking with ISPA 2006, volume 4331 of LNCS, pages 440--451, Berlin/Heidelberg, November 2006. Springer.
 
11
D. England and J. B. Weissman. Costs and benefits of load sharing in the computational Grid. In 10th International Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP '04), volume 3277 of LNCS, pages 160--175, New York, USA, 2004. Springer Berlin Heidelberg.
 
12
 
13
J. Fontán, T. Vázquez, L. Gonzalez, R. S. Montero, and I. M. Llorente. OpenNEbula: The open source virtual machine manager for cluster computing. In Open Source Grid and Cluster Software Conference - Book of Abstracts, San Francisco, USA, May 2008.
 
14
 
15
C. Grimme, J. Lepping, and A. Papaspyrou. Prospects of collaboration between compute providers by means of job interchange. In Job Scheduling Strategies for Parallel Processing, volume 4942 of Lecture Notes in Computer Science, pages 132--151, Berlin /Heidelberg, April 2008. Springer.
 
16
17
 
18
 
19
M. Islam, P. Bala ji, P. Sadayappan, and D. K. Panda. QoPS: A QoS based scheme for parallel job scheduling. In 9th International Workshop on Job Scheduling Strategies for Paral lel Processing (JSSPP'03), volume 2862 of LNCS, pages 252--268, Seattle, WA, USA, 2003. Springer.
 
20
 
21
 
22
 
23
 
24
 
25
D. Nurmi, R. Wolski, C. Crzegorczyk, G. Obertelli, S. Soman, L. Youseff, and D. Zagorodnov. Eucalyptus: a technical report on an elastic utility computing architecture linking your programs to useful systems. Technical Report 2008-10, Department of Computer Science, University of California, Santa Barbara, California, USA, 2008.
26
27
 
28
A. Rubio-Montero, E. Huedo, R. Montero, and I. Llorente. Management of virtual machines on globus Grids using GridWay. In IEEE International Parallel and Distributed Processing Symposium (IPDPS 2007), pages 1--7, Long Beach, USA, March 2007. IEEE Computer Society.
 
29
P. Ruth, P. McGachey, and D. Xu. VioCluster: Virtualization for dynamic computational domain. In IEEE International on Cluster Computing (Cluster 2005), pages 1--10, Burlington, USA, September 2005. IEEE.
 
30
A. Shoykhet, J. Lange, and P. Dinda. Virtuoso: A system for virtual machine marketplaces. Technical Report NWU-CS-04-39, Electrical Engineering and Computer Science Department, Northwestern University, Evanston/Chicago, IL, July 2004.
 
31
32
 
33
 
34
 
35
M. Tatezono, N. Maruyama, and S. Matsuoka. Making wide-area, multi-site MPI feasible using Xen VM. In Workshop on Frontiers of High Performance Computing and Networking (held with ISPA 2006), volume 4331 of LNCS, pages 387--396, Berlin/Heidelberg, 2006. Springer.
 
36
37
 
38

Collaborative Colleagues:
Marcos Dias de Assuncao: colleagues
Alexandre di Costanzo: colleagues
Rajkumar Buyya: colleagues