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Data Replication Impact on DDBS System Performance

Data Replication Impact on DDBS System Performance

Ali A. Amer
Copyright: © 2019 |Pages: 29
ISBN13: 9781522571865|ISBN10: 1522571868|ISBN13 Softcover: 9781522587231|EISBN13: 9781522571872
DOI: 10.4018/978-1-5225-7186-5.ch006
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MLA

Amer, Ali A. "Data Replication Impact on DDBS System Performance." Semantic Web Science and Real-World Applications, edited by Miltiadis D. Lytras, et al., IGI Global, 2019, pp. 134-162. https://doi.org/10.4018/978-1-5225-7186-5.ch006

APA

Amer, A. A. (2019). Data Replication Impact on DDBS System Performance. In M. Lytras, N. Aljohani, E. Damiani, & K. Chui (Eds.), Semantic Web Science and Real-World Applications (pp. 134-162). IGI Global. https://doi.org/10.4018/978-1-5225-7186-5.ch006

Chicago

Amer, Ali A. "Data Replication Impact on DDBS System Performance." In Semantic Web Science and Real-World Applications, edited by Miltiadis D. Lytras, et al., 134-162. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7186-5.ch006

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Abstract

In distributed database systems (DDBS), the utmost purpose of data distribution and replication aims at shrinking transmission costs (TC), including communication costs, and response time. In this chapter, therefore, an enhanced heuristic clustering-based technique for data fragmentation and replicated based allocation is efficaciously presented. This work is mainly sought to further enhance an existing technique so TC is to be significantly minimized. In fact, the approached enhancement is applied by suggesting different replication scenarios. Off these scenarios, one scenario is to be selected based on competitive performance evaluation process. DDBS performance is measured via its being exposed on objective function (TC). Despite the fact that this work is mildly improved, yet evaluation results show that it has been promising, particularly as TC being the foremost design objective of DDBS System. Experimental results have been analyzed under all presented scenarios as an internal evaluation and are vividly provided to demonstrate the undeniable impact of data replication on DDBS performance.

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