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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  2/2017 - 8

A New Optimized Model to Handle Temporal Data using Open Source Database

KUMAR, S. See more information about KUMAR, S. on SCOPUS See more information about KUMAR, S. on IEEExplore See more information about KUMAR, S. on Web of Science, RISHI, R. See more information about RISHI, R. on SCOPUS See more information about RISHI, R. on SCOPUS See more information about RISHI, R. on Web of Science
 
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Download PDF pdficon (1,184 KB) | Citation | Downloads: 1,136 | Views: 2,942

Author keywords
indexing, object oriented databases, open source software, query processing, runtime

References keywords
temporal(17), data(15), relational(7), databases(7), systems(6), information(6), database(6), object(5), time(4), science(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 55 - 60
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02008
Web of Science Accession Number: 000405378100008
SCOPUS ID: 85020110475

Abstract
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The majority of the database applications now a days deal with temporal data. Temporal records are known to change during the course of time and facilities to manage the multiple snapshots of these records are generally missing in conventional databases. Consequently, different temporal data models have been proposed and implemented as an extension of the temporal less database systems. In the single relation model, the present and past instances are stored in a single relation that makes its handling cumbersome and inefficient. This paper emphasize upon storing the past instances of the records in the multiple historical relations. The current relations will manage the recent snapshot of data. The tuple time stamping approach is used to timestamp the temporal records. This paper proposes a temporal model for the management of time varying data built on the top of conventional open source database. Indexing is used to enhance the performance of the model. The proposed model is also compared with the single relation model.


References | Cited By  «-- Click to see who has cited this paper

[1] F. Kunzner, D. Petkovic, "A comparison of different forms of temporal data management," Beyond Databases, Architectures and Structures. Springer International Publishing, pp 92-106, 2015.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 9]


[2] S. M. Halawani, N. A. Al-Romema, "Retrieval optimization technique for tuple timestamp historical relation temporal data model," Journal of Computer Science 8.2, pp 243-250, 2012.

[3] R. D. M. Galante, C. S. D. Santos, N. Edelweiss, A. F. Moreira, "Temporal and versioning model for schema evolution in object-oriented databases," Data & Knowledge Engineering, pp 99-128, May, 2005.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 37]


[4] C. Atay, "An attribute or tuple timestamping in bitemporal relational databases," Turkish Journal of Electrical Engineering & Computer Science, pp 4305-4321, 2016.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 5]


[5] M. Kvet, K. Matiasko, M. Vajsova, "Sensor based transaction temporal database architecture," in IEEE World Conference on Factory Communication Systems (WFCS), 2015.
[CrossRef] [SCOPUS Times Cited 8]


[6] J. Mate, J. Safarik, "Transformation of relational databases to transaction-time temporal databases," 2nd Eastern European Regional Conference on the Engineering of Computer Based Systems (ECBS-EERC), 201.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 18]


[7] I. A. Goralwalla, M. T. Ozsu, D. Szafron. "A framework for temporal data models: exploiting object-oriented technology," Proc. of IEEE TOOLS 23 on Technology of Object-Oriented Languages and Systems, 1997.
[CrossRef] [Web of Science Record]


[8] C. S. Jensen, R. T. Snodgrass, "Temporal data management," IEEE Transactions on Knowledge and Data Engineering, pp 36-44, 1999.
[CrossRef] [Web of Science Times Cited 135] [SCOPUS Times Cited 192]


[9] N. Edelweiss, P. N. Hubler, M. M. Moro, G. Demartine, "A temporal database management system implemented on top of a conventional database," Proc. XX IEEE International Conference of the Chilean Computer Science Society, 2000.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 13]


[10] C. Yang et al., "Standardization on bitemporal information representation in BCDM," IEEE International Conference on Information and Automation, 2015, pp. 2052-2057.
[CrossRef] [SCOPUS Times Cited 3]


[11] A. U. Tansel, "On handling time-varying data in the relational data model," Information and Software Technology, pp 119-126, 2004.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 12]


[12] V. T. N. Chau, S. Chittayasothorn, "A temporal compatible object relational database system," in Proc. of IEEE SoutheastCon, 2007.
[CrossRef] [SCOPUS Times Cited 10]


[13] L. Anselma, P. Terenziani, R. T. Snodgrass, "Valid-time indeterminacy in temporal relational databases: Semantics and representations," IEEE Transactions on Knowledge and Data Engineering, pp. 2880-2894, Dec. 2013.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 25]


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[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 73]


[15] S. M. Halawani, N. A. Al-Romema, "Memory storage issues of temporal database applications on relational database management systems," Journal of Computer Science, pp 296-304, 2010.

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[CrossRef]


[18] M. Pomarlan, "Visibility-based planners for mobile robots capable to handle path existence queries in temporal logic," Advances In Electrical and Computer Engineering, pp 55-64, Feb. 2014.
[CrossRef] [Full Text] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


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[20] P. Terenziani, "Irregular indeterminate repeated facts in temporal relational databases," IEEE Transactions on Knowledge and Data Engineering, pp 1075-1079, Apr. 2016.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 10]




References Weight

Web of Science® Citations for all references: 302 TCR
SCOPUS® Citations for all references: 440 TCR

Web of Science® Average Citations per reference: 14 ACR
SCOPUS® Average Citations per reference: 21 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-11-17 21:32 in 123 seconds.




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