Developing an Efficient Model for Building Data Warehouse Using Mobile Agent

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Author(s)

Tarig Mohammed Ahmed 1,* Mohammed Hassan Fadhul 1

1. Department of Computer Sciences, University of Khartoum, Sudan

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2016.09.02

Received: 8 Oct. 2015 / Revised: 23 Feb. 2016 / Accepted: 1 May 2016 / Published: 8 Sep. 2016

Index Terms

Data-warehouse, Performance, Storage, Mobile Agent

Abstract

Data-warehouse is an emerging technology with great potential. Nowadays, businesses are competing fiercely to dominate the market where profitability is promising using every available means to reach their goal. Performance and storage are big challenges in building data-warehouse focusing by researchers recent years. In this paper a new model for developing an efficient data warehouse by using mobile agent technology has been proposed. The main idea behind this model is to use the mobile agent to extract and analyze operational data in their location. So, instead of using ETL, the mobile agent will be used. After the mobile agent completing its journey among operational databases, all tasks of ETL will be performed. By this way no need high storage media to extract the data from the operational database. As cost of time, the model proves less consuming of time. The model has been implemented using .Net Framework and C# and the results have been presented and discussed.

Cite This Paper

Tarig Mohammed Ahmed, Mohammed Hassan Fadhul, "Developing an Efficient Model for Building Data Warehouse Using Mobile Agent", International Journal of Information Technology and Computer Science(IJITCS), Vol.8, No.9, pp.9-16, 2016. DOI:10.5815/ijitcs.2016.09.02

Reference

[1]H. Jiawei, K. Michleline and P. Jiane, “Data Warehouse and Online Analytical Processing 3rd Edition,” in Data Mining Concept and Techniques, Morgan Kaufmann, 2012, p. 126.

[2]Patil, Mayuri Kirange DD. "Use of ETL Subsystems for Real-Time Data-Warehouse using MS SQL Server Tool." Asian Journal of Computer Science and Information Technology 5.4 (2015): 26-32.‏

[3]Terrizzano, Ignacio, et al. "Data Wrangling: The Challenging Yourney from the Wild to the Lake." CIDR. 2015.‏

[4]J. L. Wilburt, J. Yang, C. Yiang, G. Hictor and W. Jenifer, “Performace Issue In Incremental Warehouse Maintainence,” IEEE, pp. 461-472, 2000.

[5]A. Thilini and W. Hugh, “Key Orginizational Factors In Data Warehouse Architecture Selection,” ACM, pp. 201-212, 2010.

[6]V. Rainradi, “Introduction To Data Warehouse,” in Building A Data Warehouse With Example in SQL Server, Apress, 2008, p. 10.

[7]Tarig Mohamed Ahmed, Increasing Mobile Agent Performance by Using Free Areas Mechanism.,Journal of Object Technology,6,4,125-140,2007.

[8]Marketos, Gerasimos D. Data warehousing & mining techniques for moving object databases. Diss. Ph. D. dissertation, Department of Informatics, University of Piraeus, 2009.‏

[9]J. Song, Y. Boa and J. Shi, “A Triggering and Scheduling Approach for ETL In Real-Time Data Warehouse,” IEEE, no. 2010 10th, 2010.

[10]S. Jamil and I. Rashda, “Performance Analysis of Indexing technique In Data  Warehousing,” IEEE, pp. 57-61, 2009.

[11]Weippl, E.; Altmann, J.; Essmayr, W. Mobile database agents for building data warehouses Database and Expert  Systems Applications, 2000. Proceedings. 11th International Workshop on, Pages: 477 – 481, 2000

[12]Bhan, M., Rajinikanth, K., Geetha, D. E., & S Kumar, ,T.V. (2014). DWPPT: Data warehouse performance prediction tool. International Journal of Computer  Applications, 104(13)

[13]Abdulhadi, Z. Q., Zuping, Z., & Housien, H. I. (2013). Bitmap index as effective Indexing for low cardinality column in data warehouse. International Journal of Computer Applications, 68(24) 

[14]Moudani, W., Hussein, M., Moukhtar, M., & Mora-Camino, l. (2011). Enhancement of a data warehouse performance using association rules technique. International Journal of Computer Applications, 21(7) 

[15]Ming-Chuan Hung, Man-Lin Huang, Don-Lin Yang, Nien-Lin Hsueh, Efficient approaches for materialized views selection in a data warehouse, Information Sciences, Volume 177, Issue 6, 15 March 2007, Pages 1333-1348, ISSN 0020-0255