Object Oriented Query Response Time for UML Models

Abstract

Nowadays, the size of database of any business organization is increasing and many of the companies are shifted the old structured database into the object oriented database. Due to increase of size of database complexity of database is increasing therefore, it is necessary to optimize the object oriented query response time from the complex object oriented database. In the present paper, a real case study of Life Insurance Corporation of India is taken and sample object oriented database is designed by the use of SQL Server 2008. A UML model is designed for computing the object oriented query response time. Table and graph are also represented for the computed records in five runs.

Share and Cite:

V. Saxena and S. Kumar, "Object Oriented Query Response Time for UML Models," Journal of Software Engineering and Applications, Vol. 5 No. 7, 2012, pp. 508-512. doi: 10.4236/jsea.2012.57059.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] M. Blaha and J. Rumbaugh, “Object Oriented Modeling,” 2nd Edition, Prentice Hall, Upper Saddle River, 2005.
[2] G. Booch, J. Rumbaugh and I. Jacobson, “The Unified Modeling Language User Guide,” 12th Indian Reprint, Pearson Education, Upper Saddle River, 2004.
[3] G. Booch, J. Rumbaugh and I. Jacobson, “The Unified Modeling Language User Guide,” Addison Wesley, Reading, 1999.
[4] G. Booch, “Object-Oriented Analysis and Design with Applications,” 2nd Edition, Addison Wesley, Reading, 1994.
[5] S. Cranefiel and M. Purvis, “UML as an Ontology Modeling Language,” Proceedings of the Workshop on Intelligent Information Integration, 16th International Joint Conference on Artificial Intelligence, Barcelona, 16-22 July 1999.
[6] U. Dayal, “Of Nests and Trees: A Unified Approach to Processing Queries That Contain the Nested Sub Queries, Aggregates and Quantifiers,” Proceedings of 13th VLDB Conference, Brighton, 1-4 September 1987, pp. 197-208.
[7] A. Deshpande, S. Nath, B. P. Gibbons and S. Seshan, “Cache-and-Query for Wide Area Sensor Databases,” SIGMOD’03, San Diego, 8 June 2003, pp. 503-514.
[8] R. Ganski and H. K. T. Wong, “Optimization of Nested SQL Queries Revisited,” Proceedings of SIGMOD Conference, Vol. 16, No. 3, 1987, pp. 23-33. doi:10.1145/38714.38723
[9] H. Gomaa, “Designing Concurrent, Distributed, and Real- Time Applications with UML,” Proceedings of the 23rd International Conference on Software Engineering, Toronto, 12-19 May 2001, p. 829.
[10] E. Holz, “Application of UML within the Scope of New Telecommunication Architectures,” GROOM Work-shop on UML, Physicaverlag, Mannheim, 1997.
[11] S. Huaiming, W. Yang, A. Mingyuan, W. Weiping and S. Ninghui, “Query Prediction in Large Scale Data Intensive Event Stream Analysis Systems,” 7th International Conference on Grid and Cooperative Computing, Shenzhen, 24-26 October 2008.
[12] W. Kim, “On Optimizing a SQL-like Nested Query,” ACMTODS, Vol. 7, No. 3, 1982, pp. 443-469.
[13] OMG, “UML Profile for Schedulability, Performance and Time,” OMG Document Ptc/03-02-03, Needham, 2002.
[14] OMG, “UML Superstructure Specification v 2.0,” 2005. http://www.omg.org/cgi-bin doc? Formal/
[15] OMG, “Unified Modeling Language (UML)—Version 1.5,” OMG Document Formal/2003-03-01, Needham, 2003.
[16] OMG, “Unified Modeling Language Specification,” 2011. http://www.omg.org
[17] S. Pllana and T. Fahringer, “UML Based Modeling of Performance Oriented Parallel and Distributed Applications,” Winter Simulation Conference USA, Vol. 1, 2002, pp. 497-505.
[18] P. M. Kumar, P. Kumarsen and J. Vaideeswasam, “Optimism Analysis of Parallel Queries in Databases through Multicores,” International Journal of Database Management Systems, Vol. 3, No. 1, 2011, 156 p.
[19] V. Saxena, D. Arora and S. Ahmad, “Object Oriented Distributed Architecture System through UML,” IEEE International Conference on Advanced in Computer Vision and Information Technology, Aurangabad, 28-30 November 2007, pp. 305-310.
[20] V. Saxena and G. A. Ansari, “UML Modeling & Protection of Domain Based System,” International Journal of Computer Science and Network Security, Vol. 8, No. 7, 2008, pp. 338-344.
[21] T. Wang, B. Yang, A. Huang, Q. Zhang, J. Gao, D. Yang, S. Tang and J. Niu, “Dynamic Data Migration Policies for Query-Intensive Distributed Data Environments,” APWeb/WAIM 2009, LNCS 5446, Springer-Verlag, Berlin, 2009, pp. 63-75.
[22] W. Liang, B. Chen and J. X. Yu, “Response Time Constrained Top-k Query Evaluation in Sensor Networks,” 14th IEEE International Conference on Parallel and Distributed Systems, Melbourne, 8-10 December 2008, pp. 575-582. doi:10.1109/ICPADS.2008.65
[23] S. D. Muruganathan, A. B. Sesay and W. A. Krzymien, “Analytical Query Response Time Evaluation for a Two-Level Clustering Hierarchy Based Wireless Sensor Network Routing Protocol,” Communications Letters, IEEE, Vol. 14, No. 5, 2010, pp. 486-488. doi:10.1109/LCOMM.2010.05.091473
[24] G. C. Wei and L. T. Ming, “A P2P Object-Oriented Database System That Supports Multi-Attribute and Range Queries with Improved Query Response Time,” Information Technology (ITSim), 2010 International Symposium, Kuala Lumpur, 15-17 June 2010, pp. 1250-1255.
[25] C. A. Yfoulis, A. Gounaris and D. Tzolas, “Minimization of the Response Time in Parallel Database Queries: An Adaptive Cost-Aware MPC-Based Solution,” 19th Mediterranean Conference on Control & Automation (MED), Corfu, 20-23 June 2011, pp. 813-818.
[26] R. Tavenard, H. Jegou and L. Amsaleg, “Balancing Clusters to Reduce Response Time Variability in Large Scale Image Search,” 9th International Workshop on Content-Based Multimedia Indexing (CBMI), Madrid, 13-15 June 2011, pp. 19-24. doi:10.1109/CBMI.2011.5972514
[27] Z. Y. Zhang, L. Bin and C. Zhi, “The Research on the Query Optimization on the Distributed Heterogeneous Database Based on the Response Time,” Computer Science and Network Technology, International Conference, Harbin, 24-26 December 2011, pp. 1541-1544.
[28] W. Liang, B. Chen and J. X. Yu, “Top-k Query Evaluation in Sensor Networks under Query Response Time Constraint,” Information Sciences: An International Journal, Vol. 181, No. 4, 2011, pp. 869-882. doi:10.1016/j.ins.2010.10.006
[29] N. V. Murray and E. Rosenthal, “Linear Response Time for Implicate and Implicant Queries,” Knowledge and Information Systems, Vol. 22, No. 3, 2010, pp. 287-317. doi:10.1007/s10115-009-0199-x

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.