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An Efficient Grid Method for Continuous Skyline Computation over Dynamic Data Set

  • Li, He (Department of Information and Communication Engineering Chungbuk National University) ;
  • Jang, Su-Min (Department of Computer Education Chungbuk National University) ;
  • Yoo, Kwan-Hee (Department of Computer Education Chungbuk National University) ;
  • Yoo, Jae-Soo (Department of Information and Communication Engineering Chungbuk National University)
  • Received : 2010.01.20
  • Accepted : 2010.03.15
  • Published : 2010.03.28

Abstract

Skyline queries are an important new search capability for multi-dimensional databases. Most of the previous works have focused on processing skyline queries over static data set. However, most of the real applications deal with the dynamic data set. Since dynamic data set constantly changes as time passes, the continuous skyline computation over dynamic data set becomes ever more complicated. In this paper, we propose a multiple layer grids method for continuous skyline computation (MLGCS) that maintains multiple layer grids to manage the dynamic data set. The proposed method divides the work space into multiple layer grids and creates the skyline influence region in the grid of each layer. In the continuous environment, the continuous skyline queries are only handled when the updating data points are in the skyline influence region of each layer grid. Experiments based on various data distributions show that our proposed method outperforms the existing methods.

Keywords

References

  1. S. Borzsonyi, D. Kossmann and K. Stocker, “The skyline operator,” Proc. ICDE, 2001, pp. 421-430. https://doi.org/10.1109/ICDE.2001.914855
  2. K.L. Tan, P.K. Eng and B.C. Ooi, “Efficient Progressive Skyline Computation,” Proc. VLDB, 2001, pp. 301-310
  3. D. Papadias, Y.F. Tao, G. Fu and B. Seeger, “An optimal and progressive algorithm for skyline queries,” Proc. SIGMOD, 2003, pp.467-478. https://doi.org/10.1145/872757.872814
  4. D. Papadias, Y.F. Tao, G. Fu and B. Seeger, “Progressive skyline computation in database system,” ACM Journal, vol.30, no.1, Mar. 2005, pp. 41-82. https://doi.org/10.1145/1061318.1061320
  5. W.T. Balke, U. Guntzer and J.X. Zheng, “Efficient distributed skyline for web information systems,” Proc. EDPT'04, 2004, pp.256-273. https://doi.org/10.1007/978-3-540-24741-8_16
  6. M. Morse, J.M. Patel and W.I. Grosky, “Efficient Continuous Skyline Computation,” Proc. ICDE, 2006, pp. 108-108. https://doi.org/10.1109/ICDE.2006.56
  7. X.M. Lin, Y.D. Yuan, W. Wang and H.J. Lu, “Stabbing the Sky: Efficient Skyline Computation over Sliding Windows,” Proc. ICDE, 2005, pp. 502-513. https://doi.org/10.1109/ICDE.2005.137
  8. Y.F. Tao and D. Papadias, “Maintianing sliding window skylines on data streams,” IEEE Journal, vol.18, no.3, Jan. 2006, pp. 377-391. https://doi.org/10.1109/TKDE.2006.48
  9. Z.Y. Huang, H. Lu, B.C. Ooi and Anthony K.H. Tung, “Continuous skyline queries for moving objects,” IEEE Journal, vol.18, no.12, 2006, pp. 1645-1658. https://doi.org/10.1109/TKDE.2006.185
  10. L. Tian, L. Wang, P. Zou, Y. Jia and A. Li, “Continuous Monitoring of Skyline Query over Highly Dynamic Moving Objects,” Proc. MobiDE'07, 2007, pp. 59-66. https://doi.org/10.1145/1254850.1254861
  11. L. Tian, P. Zou, A. Li and Y. Jia, “Grid Index Based Algorithm for Continuous Skyline Computation,” Chinese Journal of Computers, vol. 6, no.6, Jun. 2008, pp.998-1012.
  12. H.T. Kung, F. Luccio and F.P. Preparata, “On finding the maxima of a set of vectors,” ACM Journal, vol.22, no.4, 1975, pp. 469-476. https://doi.org/10.1145/321906.321910
  13. Jan Chomicki, Parke Godfrey, Jarek Gryz, and Dongming Liang, “Skyline with presorting,” Proc. ICDE, 2003, pp. 717-719. https://doi.org/10.1109/ICDE.2003.1260846
  14. D. Kossmann, F. Ramsak and S. Rost, “Shooting Stars in the Sky: an Online Algorithm for Skyline Queries,” Proc. VLDB, 2002, pp.275-286.

Cited by

  1. Efficient Continuous Skyline Query Processing Scheme over Large Dynamic Data Sets vol.38, pp.6, 2016, https://doi.org/10.4218/etrij.16.0116.0010