Requirements Evocation and Analysis using ETL in Cloud Environments

Authors

  • Dr. K. Purna Chand  Associate Professor, Department of CSE, B V Raju Institute of Technology, Narsapur, Telangana, India

Keywords:

Automation, Cloud, requirements, Data Warehouse, ETL

Abstract

Cloud is an efficient service provider due to its flexibility and scalability. It is very popular by providing excellent services like IAAS, SAAS, and PAAS to the users. But still the cloud remains like a black-box for most of the software engineering requirements. It is very difficult to identify and analyze the most important data which is needed to be placed in the cloud. It is a most challenging task because of the practical difficulties that arise during the configuration, execution, deployment and pre-processing of requirements. In this paper we address some of these challenges through a flexible automation framework. We have automated the processing of different users requirements as well as the storage of it in a data warehouse by using ETL.Finally, we have developed a rich web portal to navigate, visualize and analyze the collected requirements.

References

  1. Y Ioannidis, M Shivani, G Ponnekanti. ZOO: A Desktop Experiment Management Environment. In Proceedings of the 22nd VLDB Confer-ence, Mumbai(Bombay), India, 1996.
  2. K L. Karavanic, B P. Miller. Experiment management support for performance tuning. In Proceedings of the 1997 ACM/IEEE conference on Supercomputing, Mumbai(Bombay), India, 1996.
  3. R Prodan, T Fahringer. ZEN: A Directive-based Language for Automatic Experiment Management of Distributed and Parallel Programs. In ICPP 2002, Vancouver, Canada.
  4. R Prodan, T Fahringer. ZENTURIO: An Experiment Management System for Cluster and Grid Computing. In Cluster 2002.
  5. Y Wang, A Carzaniga, A L. Wolf. Four Enhancements to Automated Distributed System Experimentation Methods. In ICSE 2008.
  6. S Babu, N Borisov, S Duan, H Herodotou, V Thummala. Automated Experiment-Driven Management of (Database) Systems. In HotOS 2009, Monte Verita, Switzeland.
  7. A Fox, W Sobel, H Wong, J Nguyen, S Subramanyam, A Sucharitakul, S Patil, D Patterson. Cloudstone: Multi-Platform, Multi-Language Benchmark and Measurement tools for Web 2.0. In CCA 2008.
  8. Y. Wang, M.J. Rutherford, A. Carzaniga, and A. L. Wolf. Automating Experimentation on Distributed Testbeds. In ASE 2005.
  9. RUBiS: Rice University Bidding System. http://rubis.ow2.org/.
  10. Open Cirrus: Open Cloud Computing Research Testbed. https:// opencirrus.org/.
  11. WIPRO Technologies. www.wipro.com/.
  12. Amazon Elastic Compute Cloud. http://aws.amazon.com.
  13. Cai, Y., Grundy, J., and Hosking, J. Experiences Integrating and Scaling a Performance Test Bed Generator with an Open Source CASE Tool. In ASE 2004.
  14. Sarkar, S. Model driven programming using XSLT: an approach to rapid development of domain-specific program generators In www.XML-JOURNAL.com. August 2002.
  15. Grundy, J., Cai, Y., and Liu, A. SoftArch/MTE: generating distributed system test-beds from high-level software architecture descriptions. In ASE 2001.
  16. Malkowski, S., Hedwig, M., and Pu, C. Experimental evaluation of N-tier systems: Observation and analysis of multi-bottlenecks. In IISWC 2009.
  17. Jayasinghe, D., Malkowski, S., Wang, Q., Li, J., Xiong, P., and Pu, C. Variations in performance and scalability when migrating n-tier appli-cations to different clouds. CLOUD 2011.
  18. Wang, Q., Malkowski, S., Jayasinghe, D., Xiong, P., Pu, C., Kane-masa, Y., Kawaba, M., and Harada, L. Impact of soft resource allocation on n-tier application scalability. IPDPS 2011.
  19. Vassiliadis, Panos. A Survey of Extract-Transform-Load Technology. Integrations of Data Warehousing, Data Mining and Database Technolo-gies: Innovative Approaches (2011).
  20. Baumgartner, R., Wolfgang, G., and Gottlob, G.,. Web Data Extraction System. Encyclopedia of Database Systems (2009): 3465-3471.
  21. Kohavi, R., Henne, R.M., Sommerfield, D. Practical guide to controlled experiments on the web: Listen to your customers not to the HiPPO. In ACM KDD 2007.
  22. Malkowski, S., Jayasinghe, D., Hedwig, M., Park, J., Kanemasa, Y., and Pu, C. Empirical analysis of database server scalability using an n-tier benchmark with read-intensive workload. ACM SAC 2010.
  23. Malkowski, S., Kanemasay, Y., Chen, H., Yamamotoz, M., Wang, Q., Jayasinghe,D., Pu,C., and Kawaba, M., Challenges and Opportunities in Consolidation at High Resource Utilization: Non-monotonic Response Time Variations in n-Tier Applications. IEEE Cloud 2012.

Downloads

Published

2018-02-28

Issue

Section

Research Articles

How to Cite

[1]
Dr. K. Purna Chand, " Requirements Evocation and Analysis using ETL in Cloud Environments, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.1597-1603, January-February-2018.