Introducing PRECIP: An API for managing repeatable experiments in the cloud

Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom

Volumn 2, Issue , 2013, Pages 19-26

  Azarnoosh, Sepideh ^a   Rynge, Mats ^a   Juve, Gideon ^a   Deelman, Ewa ^a   Nieć, Michal ^b   Malawski, Maciej ^b   Silva, Rafael Ferreira Da ^c  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b AGH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Poland)

^c UNIVERSITÉ DE LYON   (France)

Author keywords

Amazon EC2; Cloud; Cloud Provisioning; Eucalyptus; Experiment Management; Nimbus; OpenStack

Indexed keywords

CLOUD COMPUTING; CLOUDS; HIGH LEVEL LANGUAGES;

AMAZON EC2; EUCALYPTUS; EXPERIMENT MANAGEMENT; NIMBUS; OPENSTACK;

EXPERIMENTS;

EID: 84899755409     PISSN: 23302194     EISSN: 23302186     Source Type: Conference Proceeding    
DOI: 10.1109/CloudCom.2013.98     Document Type: Conference Paper

References (20)

1. Y. Jiang, C. Perng, T. Li, and R. Chang, "ASAP: A Self-Adaptive Prediction System for Instant Cloud Resource Demand Provisioning," IEEE 11th International Conference on in Data Mining (ICDM), 2011, pp. 1104-1109.
2. G. Fox, G. von Laszewski, J. Diaz, K. Keahey, J. Fortes, R. Figueiredo, S. Smallen, W. Smith, and A. Grimshaw, "FutureGrid-a reconfigurable testbed for Cloud, HPC, and Grid Computing," in Contemporary High Performance Computing: From Petascale toward Exascale, J. Vetter, Ed. Chapman & Hall, 2013.
3. G. von Laszewski, G. C. Fox, F. Wang, A. J. Younge, A. Kulshrestha, G. G. Pike, W. Smith, J. Vöckler, R. J. Figueiredo, J. Fortes, and K. Keahey, "Design of the FutureGrid experiment management framework," in Gateway Computing Environments Workshop (GCE), 2010, 2010, pp. 1-10.
4. "FutureGrid Project Statistics," Jul-2013. [Online]. Available: https://portal.futuregrid.org/projects-statistics.
5. "OpenStack," Jul-2013. [Online]. Available: http://www.openstack.org/.
6. D. Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman, L. Youseff, and D. Zagorodnov, "The eucalyptus open-source cloudcomputing system," in Cluster Computing and the Grid, 2009. CCGRID'09, pp. 124-131.
7. K. Keahey and T. Freeman, "Nimbus or an Open Source Cloud Platform or the Best Open Source EC2 No Money Can Buy.," Supercomputing 2008.
8. J. Dean and S. Ghemawat, "MapReduce: simplified data processing on large clusters," Commun Acm, vol. 51, no. 1, pp. 107-113, Jan. 2008.
9. T. White, Hadoop: The Definitive Guide, 1st ed. O'Reilly Media, Inc., 2009.
10. "Boto: A Python interface to Amazon Web Services," Sep-2013.
11. [Online]. Available: https://github.com/boto/boto.
12. "Paramiko: Python SSH module," Jul-2013. [Online]. Available: https://github.com/paramiko/paramiko.
13. B. Tierney, W. Johnston, B. Crowley, G. Hoo, C. Brooks, and D. Gunter, "The NetLogger Methodology for High Performance Distributed Systems Performance Analysis," in Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing, Washington, DC, USA, 1998, p. 260.
14. "MongoDB," Jul-2013. [Online]. Available: http://www.mongodb. org/.
15. M. Malawski, J. Meizner, M. Bubak, and P. Gepner, "Component Approach to Computational Applications on Clouds," Procedia Comput. Sci., vol. 4, pp. 432-441, 2011.
16. E. Dede, M. Govindaraju, D. Gunter, R. S. Canon, and L. Ramakrishnan, "Performance evaluation of a MongoDB and hadoop platform for scientific data analysis," in Proceedings of the 4th ACM workshop on Scientific cloud computing, New York, NY, 2013, pp. 13-20.
17. G. Juve and E. Deelman, "Wrangler: virtual cluster provisioning for the cloud," in Proceedings of the 20th international symposium on High performance distributed computing, NY, USA, 2011, pp. 277-278.
18. Y. Ioannidis, M. Livny, S. Gupta, and N. Ponnekanti, "ZOO: A Desktop Experiment Management Environment," in In Proc. 22nd International VLDB Conference, 1996, pp. 274-285.
19. "Moses-Experiment Management System," Jul-2013. [Online]. Available: http://www.statmt.org/moses/?n=FactoredTraining.EMS.
20. C. Türker, E. Stolte, D. Joho, and R. Schlapbach, "B-Fabric: A Data and Application Integration Framework for Life Sciences Research," in Data Integration in the Life Sciences, vol. 4544, S. Cohen-Boulakia and V. Tannen, Eds. Springer Berlin Heidelberg, 2007, pp. 37-47.