Constructing elastic scientific applications using elasticity primitives

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7975 LNCS, Issue PART 5, 2013, Pages 281-294

  Galante, Guilherme ^a   Bona, Luis Carlos Erpen ^a  

^a FEDERAL UNIVERSITY OF PARANÁ   (Brazil)

Author keywords

Cloud computing; elasticity; scientific applications

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLOUD COMPUTING; COMPUTER SCIENCE; COMPUTERS;

BASIC BUILDING BLOCK; COMPUTING RESOURCE; DYNAMIC ALLOCATIONS; ELASTIC APPLICATIONS; PROGRAMMING MODELS; SCIENTIFIC APPLICATIONS; VIRTUAL CLUSTERS; VIRTUAL PROCESSOR;

ELASTICITY;

EID: 85099486547     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-39640-3_21     Document Type: Conference Paper

References (27)

1. Villamizar, M., Castro, H., Mendez, D.: E-Clouds: A SaaS Marketplace for Scientific Computing. In: Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing, UCC 2012, pp. 13-20. IEEE Computer Society (2012)
2. Badger, L., Patt-Corner, R., Voas, J.: DRAFT Cloud Computing Synopsis and Recommendations Recommendations of the National Institute of Standards and Technology. Nist Special Publication 146 (2011)
3. Leymann, F.: Cloud Computing: The Next Revolution in IT. In: Proc. 52th Photogrammetric Week, pp. 3-12. Wichmann (September 2009)
4. Chieu, T.C., Mohindra, A., Karve, A.A., Segal, A.: Dynamic Scaling of Web Applications in a Virtualized Cloud Computing Environment. In: Proceedings of the 2009 IEEE International Conference on e-Business Engineering, ICEBE 2009, pp. 281-286. IEEE (2009)
5. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, A., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A View of Cloud Computing. Commun. ACM 53(4) (April 2010)
6. Wang, L., Zhan, J., Shi, W., Liang, Y.: In Cloud, Can Scientific Communities Benefit from the Economies of Scale? IEEE Transactions on Parallel and Distributed Systems 23(2), 296-303 (2012)
7. Oliveira, D., Baio, F.A., Mattoso, M.: Migrating Scientific Experiments to the Cloud. HPC in the Cloud, http://www.hpcinthecloud.com/hpccloud/2011-03- 04/migrating scientific expe
8. Galante, G., Bona, L.C.E.: A Survey on Cloud Computing Elasticity. In: Proceedings of the International Workshop on Clouds and eScience Applications Management, CloudAM 2012, pp. 263-270. IEEE/ACM (2012)
9. Chohan, N., Castillo, C., Spreitzer, M., Steinder, M., Tantawi, A., Krintz, C.: See Spot Run: Using Spot Instances for Mapreduce Workflows. In: Proceedings of the 2nd USENIX conference on Hot Topics in Cloud Computing, HotCloud 2010. USENIX Association (2010)
10. Amazon Web Services, http://aws.amazon.com/
11. Microsoft Azure, http://www.windowsazure.com/
12. Rackspace, http://www.rackspace.com/
13. Vaquero, L.M., Rodero-Merino, L., Buyya, R.: Dynamically Scaling Applications in the Cloud. SIGCOMM Comput. Commun. Rev. 41, 45-52 (2011)
14. Byun, E.K., Kee, Y.S., Kim, J.S., Maeng, S.: Cost Optimized Provisioning of Elastic Resources for Application Workflows. Future Gener. Comput. Syst. 27(8), 1011-1026 (2011)
15. Iordache, A., Morin, C., Parlavantzas, N., Riteau, P.: Resilin: Elastic MapReduce over Multiple Clouds. Technical Report RR-8081, INRIA (2012)
16. Raveendran, A., Bicer, T., Agrawal, G.: A Framework for Elastic Execution of Existing MPI Programs. In: International Symposium on Parallel and Distributed Processing Workshops and PhD Forum, IPDPSW 2011, pp. 940-947. IEEE (2011)
17. Rajan, D., Canino, A., Izaguirre, J.A., Thain, D.: Converting a High Performance Application to an Elastic Cloud Application. In: 3rd International Conference on Cloud Computing Technology and Science, CLOUDCOM 2011, pp. 383-390. IEEE (2011)
18. GoGrid, http://www.gogrid.com/
19. Caron, E., Rodero-Merino, L.F., Desprez, A.M.: Auto-Scaling, Load Balancing and Monitoring in Commercial and Open-Source Clouds. Technical Report 7857, INRIA (2012)
20. Google App Engine, http://code.google.com/appengine
21. Lim, H.C., Babu, S., Chase, J.S., Parekh, S.S.: Automated Control in Cloud Computing: Challenges and Opportunities. In: 1st Workshop on Automated Control for Datacenters and Clouds, ACDC 2009, pp. 13-18. ACM (2009)
22. Roy, N., Dubey, A., Gokhale, A.: Efficient Autoscaling in the Cloud Using Predictive Models for Workload Forecasting. In: 4th International Conference on Cloud Computing, CLOUD 2011, pp. 500-507. IEEE (2011)
23. Gong, Z., Gu, X., Wilkes, J.: PRESS: PRedictive Elastic ReSource Scaling for Cloud Systems. In: 6th International Conference on Network and Service Management, CNSM 2010, pp. 9-16. IEEE (2010)
24. Sharma, U., Shenoy, P., Sahu, S., Shaikh, A.: A Cost-Aware Elasticity Provisioning System for the Cloud. In: Proceedings of the 31st International Conference on Distributed Computing Systems, ICDCS 2011, pp. 559-570. IEEE (2011)
25. Calheiros, R.N., Vecchiola, C., Karunamoorthy, D., Buyya, R.: The Aneka Platform and Qos-Driven Resource Provisioning for Elastic Applications on Hybrid Clouds. Future Generation Computer Systems 28(6), 861-870 (2011)
26. Yu, L., Thain, D.: Resource Management for Elastic Cloud Workflows. In: Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2012, pp. 775-780. IEEE (2012)
27. OpenNebula, http://www.opennebula.org/