This Article 
 Bibliographic References 
 Add to: 
Multicloud Deployment of Computing Clusters for Loosely Coupled MTC Applications
June 2011 (vol. 22 no. 6)
pp. 924-930
Rafael Moreno-Vozmediano, Universidad Complutense de Madrid, Madrid
Ruben S. Montero, Universidad Complutense de Madrid, Madrid
Ignacio M. Llorente, Universidad Complutense de Madrid, Madrid
Cloud computing is gaining acceptance in many IT organizations, as an elastic, flexible, and variable-cost way to deploy their service platforms using outsourced resources. Unlike traditional utilities where a single provider scheme is a common practice, the ubiquitous access to cloud resources easily enables the simultaneous use of different clouds. In this paper, we explore this scenario to deploy a computing cluster on the top of a multicloud infrastructure, for solving loosely coupled Many-Task Computing (MTC) applications. In this way, the cluster nodes can be provisioned with resources from different clouds to improve the cost effectiveness of the deployment, or to implement high-availability strategies. We prove the viability of this kind of solutions by evaluating the scalability, performance, and cost of different configurations of a Sun Grid Engine cluster, deployed on a multicloud infrastructure spanning a local data center and three different cloud sites: Amazon EC2 Europe, Amazon EC2 US, and ElasticHosts. Although the testbed deployed in this work is limited to a reduced number of computing resources (due to hardware and budget limitations), we have complemented our analysis with a simulated infrastructure model, which includes a larger number of resources, and runs larger problem sizes. Data obtained by simulation show that performance and cost results can be extrapolated to large-scale problems and cluster infrastructures.

[1] I. Raicu, I. Foster, and Y. Zhao, “Many-Task Computing for Grids and Supercomputers,” Proc. Workshop Many-Task Computing on Grids and Supercomputers, pp. 1-11, 2008.
[2] BioTeam “Howto: Unicluster and Amazon EC2,” technical report, BioTeam Lab Summary, 2008.
[3] I. Llorente, R. Moreno-Vozmediano, and R. Montero, “Cloud Computing for On-Demand Grid Resource Provisioning,” Advances in Parallel Computing, vol. 18, pp. 177-191, IOS Press, 2009.
[4] Amazon Elastic Compute Cloud,, 2010.
[5] ElasticHosts, http:/, 2010.
[6] E. Walker, “The Real Cost of a CPU Hour,” Computer, vol. 42, no. 4, pp. 35-41, Apr. 2009.
[7] M.A. Frumkin and R.F. Van der Wijngaart, “NAS Grid Benchmarks: A Tool for Grid Space Exploration,” J. Cluster Computing, vol. 5, no. 3, pp. 247-255, 2002.
[8] R.S. Montero, R. Moreno-Vozmediano, and I.M. Llorente, “An Elasticity Model for High Throughput Computing Clusters,” to be published in J. Parallel and Distributed Computing, doi: 10.1016/j.jpdc.2010.05.005, 2010.
[9] E. Walker, J. Gardner, V. Litvin, and E. Turner, “Creating Personal Adaptive Clusters for Managing Scientific Jobs in a Distributed Computing Environment,” Proc. IEEE Second Int'l Workshop Challenges of Large Applications in Distributed Environments (CLADE '06).
[10] I. Raicu, Y. Zhao, C. Dumitrescu, I. Foster, and M. Wilde, “Falkon: A Fast and Light-Weight TasK ExecutiON Farmework,” Proc. IEEE/ACM Conf. SuperComputing, 2007.
[11] E. Huedo, R.S. Montero, and I.M. Llorente, “The GridWay Framework for Adaptive Scheduling and Execution on Grids,” Scalable Computing—Practice and Experience, vol. 6, pp. 1-8, 2006.
[12] J. Chase, D. Irwin, L. Grit, J. Moore, and S. Sprenkle, “Dynamic Virtual Clusters in a Grid Site Manager,” Proc. 12th IEEE Symp. High Performance Distributed Computing, 2003.
[13] P. Ruth, P. McGachey, and D. Xu, “VioCluster: Virtualization for Dynamic Computational Domains,” Proc. IEEE Int'l Conf. Cluster Computing, 2005.
[14] I. Foster, T. Freeman, K. Keahey, D. Scheftner, B. Sotomayor, and X. Zhang, “Virtual Clusters for Grid Communities,” Proc. Sixth IEEE Int'l Symp. Cluster Computing and the Grid, 2006.
[15] M. Murphy, B. Kagey, M. Fenn, and S. Goasguen, “Dynamic Provisioning of Virtual Organization Clusters,” Proc. Ninth IEEE Int'l Symp. Cluster Computing and the Grid, 2009.
[16] J. Fronckowiak, “Auto-Scaling Web Sites Using Amazon EC2 and Scalr,” Amazon EC2 Articles and Tutorials, 2008.
[17] A. Aboulnaga, K. Salem, A. Soror, U. Minhas, P. Kokosielis, and S. Kamath, “Deploying Database Appliances in the Cloud,” Bull. of the IEEE Computer Soc. Technical Committee on Data Eng., vol. 32, no. 1, pp. 13-20, 2009.
[18] A. Azeez, Autoscaling Axis2 Web Services on Amazon EC2: ApacheCon Europe, 2009.
[19] K. Keahey, M. Tsugawa, A. Matsunaga, and J. Fortes, “Sky Computing,” IEEE Internet Computing vol. 13, no. 5, pp. 43-51, Sept./Oct. 2009.

Index Terms:
Cloud computing, computing cluster, multicloud infrastructure, loosely coupled applications.
Rafael Moreno-Vozmediano, Ruben S. Montero, Ignacio M. Llorente, "Multicloud Deployment of Computing Clusters for Loosely Coupled MTC Applications," IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 6, pp. 924-930, June 2011, doi:10.1109/TPDS.2010.186
Usage of this product signifies your acceptance of the Terms of Use.