Advertisement

Journal of Computer Science and Technology

, Volume 23, Issue 1, pp 103–111 | Cite as

Efficient Optimization of Multiple Subspace Skyline Queries

  • Zhen-Hua HuangEmail author
  • Jian-Kui Guo
  • Sheng-Li Sun
  • Wei Wang
Regular Paper

Abstract

We present the first efficient sound and complete algorithm (i.e., AOMSSQ) for optimizing multiple subspace skyline queries simultaneously in this paper. We first identify three performance problems of the naíve approach (i.e., SUBSKY) which can be used in processing arbitrary single-subspace skyline query. Then we propose a cell-dominance computation algorithm (i.e., CDCA) to efficiently overcome the drawbacks of SUBSKY. Specially, a novel pruning technique is used in CDCA to dramatically decrease the query time. Finally, based on the CDCA algorithm and the share mechanism between subspaces, we present and discuss the AOMSSQ algorithm and prove it sound and complete. We also present detailed theoretical analyses and extensive experiments that demonstrate our algorithms are both efficient and effective.

Keywords

skyline query query optimization regular grid performance evaluation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

11390_2008_Article_9112_ESM.pdf (95 kb)
(PDF 95 kb)

References

  1. [1]
    Borzsonyi S, Kossmann D, Stocker K. The skyline operator. In Proc. ICDE, Heidelberg, Germany, April 2–6, 2001, pp.564–573.Google Scholar
  2. [2]
    Jin W, Han J, Ester M. Mining Thick skylines over large databases. In Proc. PKDD, Pisa, Italy, Sept. 20–24, 2004, pp.372–384.Google Scholar
  3. [3]
    Hristidis V, Koudas N, Papakonstantinou Y. PREFER: A system for the efficient execution of multi-parametric ranked queries. In Proc. SIGMOD, California, USA, May 21–24, 2001, pp.249–260.Google Scholar
  4. [4]
    Agrawal R, Wimmers E L. A framework for expressing and combining preferences. In Proc. SIGMOD, Texas, USA, May 14–19, 2000, pp.455–466.Google Scholar
  5. [5]
    Chomicki J, Godfrey P, Gryz J, Liang D. Skyline with pre-sorting. In Proc. ICDE, Bangalore, India, Mar. 5–8, 2003, pp.816–825.Google Scholar
  6. [6]
    Tan K L, Eng P K, Ooi B C. Efficient progressive skyline computation. In Proc. VLDB, Rome, Italy, Sept. 11–14, 2001, pp.631–642.Google Scholar
  7. [7]
    Kossmann D, Ramsak F, Preparata F P. Shooting stars in the sky: An online algorithm for skyline queries. In Proc. VLDB, Rome, Italy, Sept. 11–14, 2001, pp.673–682.Google Scholar
  8. [8]
    Papadias D, Tao Y, Fu G, Seeger B. An optimal and progressive algorithm for skyline queries. In Proc. SIGMOD, California, USA, June 9–12, 2003, pp.391–402.Google Scholar
  9. [9]
    Balke W T, Guntzer U, Zheng J X. Efficient distributed skylining for web information systems. In Proc. EDBT, Heraklion, Greece, Mar. 14–18, 2004, pp.523–541.Google Scholar
  10. [10]
    Tao Y F, Xiao X K, Pei J. SUBSKY: Efficient computation of skylines in subspaces. In Proc. ICDE, Atlanta, USA, April 3–8, 2006, pp.711–720.Google Scholar
  11. [11]
    Pei J, Jin W, Ester M, Tao Y. Catching the best views of skyline: A semantic approach based on decisive subspaces. In Proc. VLDB, Trondheim, Norway, Aug. 30–Sep. 2, 2005, pp.315–326.Google Scholar
  12. [12]
    Yuan Y, Lin X, Liu Q, Wang W, Yu J X, Zhang Q. Efficient computation of the skyline cube. In Proc. VLDB, Trondheim, Norway, Aug. 30–Sept. 2, 2005, pp.368–379.Google Scholar
  13. [13]
    Xiong X, Mokbel M F. SEA-CNN: Scalable processing of continuous K-NN queries in spatio-temporal databases. In Proc. ICDE, Tokyo, Japan, Apr. 5–8, 2005, pp.643–654.Google Scholar
  14. [14]
    Das A, Gehrke J, Riedewald M. Approximate join processing over data streams. In Proc. SIGMOD, California, USA, June 9–12 2003, pp.362–374.Google Scholar

Copyright information

© Science Press, Beijing, China and Springer Science + Business Media, LLC, USA 2008

Authors and Affiliations

  • Zhen-Hua Huang
    • 1
    Email author
  • Jian-Kui Guo
    • 1
  • Sheng-Li Sun
    • 1
  • Wei Wang
    • 1
  1. 1.Department of Computing and Information TechnologyFudan UniversityShanghaiChina

Personalised recommendations