Volume 3 Number 6 (Dec. 2013)
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IJEEEE 2013 Vol.3(6): 492-496 ISSN: 2010-3654
DOI: 10.7763/IJEEEE.2013.V3.285

An Efficient Query Processing Algorithm for Multiple Constrained Skyline Queries

I-Fang Su, Yu-Chi Chung, Yuan-Ko Huang, and Chang-Ming Tsai
Abstract— A multi-query optimization issue for constrained skyline query processing is studied in this paper. In traditional skyline query processing, each query is processed independently. In this paper, we exploit the dependencies among a collection of concurrent constrained skyline queries and design a framework to speed-up the processing of multiple constrained skyline queries. To the best of our knowledge, this is the first work to study the multi-query optimization for multiple constrained skyline queries. Based on the BBS (Branch and Bound Skyline) algorithm, we design a Multiple-Constrained-Skyline-Query (MCSQ) algorithm than can speed-up the query processing performance for multiple constrained skyline queries. We also conduct a series of experiments to evaluate the performance of our design. The result shows the efficiency of our algorithm.

Index Terms— Constrained skyline queries, database, query processing, multi-query optimization.

Fang Su is with MIS of Fortune Institute of Technology, Taiwan (ifangsu@fotech.edu.tw).
Yu-Chi Chung and Chang-Ming Tsai are with Department of Computer Science and Information Engineering of Chang Jung Christian University, Taiwan (justim@mail.cjcu.edu.tw, tsai@mail.cjcu.edu.tw).
Yuan-Ko Huang is with Department of Communication of KAO YUAN University, Taiwan (huangyk@cc.kyu.edu.tw).

Cite: I-Fang Su, Yu-Chi Chung, Yuan-Ko Huang, and Chang-Ming Tsai, " An Efficient Query Processing Algorithm for Multiple Constrained Skyline Queries," International Journal of e-Education, e-Business, e-Management and e-Learning vol. 3, no. 6, pp. 492-496, 2013.

General Information

ISSN: 2010-3654 (Online)
Abbreviated Title: Int. J. e-Educ. e-Bus. e-Manag. e-Learn.
Frequency: Quarterly
Editor-in-Chief: Prof. Kuan-Chou Chen
Executive Editor: Ms. Nancy Lau
Abstracting/ Indexing: EBSCO, Google Scholar, Electronic Journals Library, QUALIS, ProQuest, INSPEC (IET)
E-mail: ijeeee@iap.org
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