World Wide Web

, Volume 19, Issue 4, pp 545–577 | Cite as

Efficient processing of top-k dominating queries in distributed environments

  • Daichi Amagata
  • Yuya Sasaki
  • Takahiro Hara
  • Shojiro Nishio
Article

Abstract

Due to the recent massive data generation, preference queries are becoming an increasingly important for users because such queries retrieve only a small number of preferable data objects from a huge multi-dimensional dataset. A top-k dominating query, which retrieves the k data objects dominating the highest number of data objects in a given dataset, is particularly important in supporting multi-criteria decision making because this query can find interesting data objects in an intuitive way exploiting the advantages of top-k and skyline queries. Although efficient algorithms for top-k dominating queries have been studied over centralized databases, there are no studies which deal with top-k dominating queries in distributed environments. The recent data management is becoming increasingly distributed, so it is necessary to support processing of top-k dominating queries in distributed environments. In this paper, we address, for the first time, the challenging problem of processing top-k dominating queries in distributed networks and propose a method for efficient top-k dominating data retrieval, which avoids redundant communication cost and latency. Furthermore, we also propose an approximate version of our proposed method, which further reduces communication cost. Extensive experiments on both synthetic and real data have demonstrated the efficiency and effectiveness of our proposed methods.

Keywords

Top-k dominating queries Skyline Multi-dimensional data Distributed databases 

References

  1. 1.
    Akbarinia, R., Pacitti, E., Valduriez, P.: Reducing network traffic in unstructured p2p systems using top-k queries. Distributed and Parallel Databases 19(2), 67–86 (2006)CrossRefGoogle Scholar
  2. 2.
    Akbarinia, R., Pacitti, E., Valduriez, P.: Best position algorithms for top-k queries VLDB, pp. 495–506 (2007)Google Scholar
  3. 3.
    Balke, W.T., Kießling, W.: Optimizing multi-feature queries for image databases VLDB, pp. 10–14 (2000)Google Scholar
  4. 4.
    Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator, ICDE, pp. 421–430 (2001)Google Scholar
  5. 5.
    Buckley, C., Voorhees, E.M.: Evaluating evaluation measure stability SIGIR, pp. 33–40 (2000)Google Scholar
  6. 6.
    Chan, C.Y., Jagadish, H., Tan, K.L., Tung, A.K., Zhang, Z.: Finding k-dominant skylines in high dimensional space SIGMOD, pp. 503–514 (2006)Google Scholar
  7. 7.
    Chan, C.Y., Jagadish, H., Tan, K.L., Tung, A.K., Zhang, Z.: On high dimensional skylines EDBT, pp. 478–495 (2006)Google Scholar
  8. 8.
    Chen, L., Cui, B., Lu, H.: Constrained skyline query processing against distributed data sites. IEEE TKDE 23(2), 204–217 (2011)Google Scholar
  9. 9.
    Han, X., Li, J., Gao, H.: Tdep: efficiently processing top-k dominating query on massive data. Knowledge and Information Systems Springer (2014)Google Scholar
  10. 10.
    He, Z., Lo, E.: Answering why-not questions on top-k queries ICDE, pp. 750–761 (2012)Google Scholar
  11. 11.
    Hose, K., Vlachou, A.: A survey of skyline processing in highly distributed environments. The VLDB J. 21(3), 359–384 (2012)CrossRefGoogle Scholar
  12. 12.
    Huang, Z., Jensen, C.S., Lu, H., Ooi, B.C.: Skyline queries against mobile lightweight devices in manets ICDE, p. 66 (2006)Google Scholar
  13. 13.
    Ilyas, I.F., Beskales, G., Soliman, M.A.: A survey of top-k query processing techniques in relational database systems. ACM Comput. Surveys (CSUR) 40(4), 11 (2008)CrossRefGoogle Scholar
  14. 14.
    Kießling, W.: Foundations of preferences in database systems, VLDB, pp. 311–322 (2002)Google Scholar
  15. 15.
    Kontaki, M., Papadopoulos, A.N., Manolopoulos, Y.: Continuous top-k dominating queries in subspaces, Panhellenic Conference on Informatics, pp. 31–35 (2008)Google Scholar
  16. 16.
    Kontaki, M., Papadopoulos, A.N., Manolopoulos, Y.: Continuous top-k dominating queries. IEEE TKDE 24(5), 840–853 (2012)Google Scholar
  17. 17.
    Kosmatopoulos, A., Papadopoulos, A., Tsichlas, K.: Dynamic processing of dominating queries with performance guarantees ICDT, pp. 225–234 (2014)Google Scholar
  18. 18.
    Lee, J., You, G.W., Hwang, S.W.: Personalized top-k skyline queries in high-dimensional space. Inf. Syst. 34(1), 45–61 (2009)CrossRefGoogle Scholar
  19. 19.
    Lian, X., Chen, L.: Top-k dominating queries in uncertain databases EDBT, pp. 660–671 (2009)Google Scholar
  20. 20.
    Lian, X., Chen, L.: Probabilistic top-k dominating queries in uncertain databases. Inf. Sci. 226, 23–46 (2013)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Lin, X., Yuan, Y., Zhang, Q., Zhang, Y.: Selecting stars: The k most representative skyline operator, SIGMOD, pp. 86–95 (2007)Google Scholar
  22. 22.
    Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. ACM Trans. Database Syst. 30(1), 41–82 (2005)CrossRefGoogle Scholar
  23. 23.
    Santoso, B., Chiu, G.: Close dominance graph: An efficient framework for answering continuous top-k dominating queries IEEE TKDE (2013)Google Scholar
  24. 24.
    Sarma, A.D., Lall, A., Nanongkai, D., Lipton, R.J., Xu, J.: Representative skylines using threshold-based preference distributions ICDE, pp. 387–398 (2011)Google Scholar
  25. 25.
    Skoutas, D., Sacharidis, D., Simitsis, A., Kantere, V., Sellis, T.: Top-k dominant web services under multi-criteria matching EDBT, pp. 898–909 (2009)Google Scholar
  26. 26.
    Tao, Y., Ding, L., Lin, X., Pei, J.: Distance-based representative skyline ICDE, pp. 892–903 (2009)Google Scholar
  27. 27.
    Tao, Y., Xiao, X., Pei, J.: Subsky: Efficient computation of skylines in subspaces ICDE, pp. 65–76 (2006)Google Scholar
  28. 28.
    Tiakas, E., Valkans, G., Papadopoulos, A.N., Manolopoulos, Y.D.G.: Metric-based top-k dominating queries EDBT, pp. 415–426 (2014)Google Scholar
  29. 29.
    Vlachou, A., Doulkeridis, C., Halkidi, M.: Discovering representative skyline points over distributed data Scientific and Statistical Database Management, pp. 141–158. Springer (2012)Google Scholar
  30. 30.
    Vlachou, A., Doulkeridis, C., Kotidis, Y., Vazirgiannis, M.: Skypeer: Efficient subspace skyline computation over distributed data ICDE, pp. 416–425 (2007)Google Scholar
  31. 31.
    Vlachou, A., Doulkeridis, C., Nørvåg, K.: Distributed top-k query processing by exploiting skyline summaries. Distributed and Parallel Databases 30(3-4), 239–271 (2012)CrossRefGoogle Scholar
  32. 32.
    Vlachou, A., Doulkeridis, C., Nørvåg, K., Vazirgiannis, M.: On efficient top-k query processing in highly distributed environments, SIGMOD, pp. 753–764 (2008)Google Scholar
  33. 33.
    Xie, X., Lu, H., Chen, J., Shang, S.: Top-k neighborhood dominating query DASFAA, pp. 131–145 (2013)Google Scholar
  34. 34.
    Yiu, M.L., Mamoulis, N.: Efficient processing of top-k dominating queries on multi-dimensional data VLDB, pp. 483–494 (2007)Google Scholar
  35. 35.
    Yiu, M.L., Mamoulis, N.: Multi-dimensional top-k dominating queries. The VLDB J. 18(3), 695–718 (2009)CrossRefGoogle Scholar
  36. 36.
    Zhan, L., Zhang, Y., Zhang, W., Lin, X.: Identifying top k dominating objects over uncertain data DASFAA, pp. 388–405 (2014)Google Scholar
  37. 37.
    Zhang, W., Lin, X., Zhang, Y., Pei, J., Wang, W.: Threshold-based probabilistic top-k dominating queries. The VLDB J. 19(2), 283–305 (2010)CrossRefGoogle Scholar
  38. 38.
    Zhang, W., Lin, X., Zhang, Y., Pei, J., Wang, W.: Progressive processing of subspace dominating queries. The VLDB J. 20(6), 921–948 (2011)CrossRefGoogle Scholar
  39. 39.
    Zhu, L., Tao, Y., Zhou, S.: Distributed skyline retrieval with low bandwidth consumption. IEEE TKDE 21(3), 384–400 (2009)Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Daichi Amagata
    • 1
  • Yuya Sasaki
    • 2
  • Takahiro Hara
    • 1
  • Shojiro Nishio
    • 1
  1. 1.Department of Multimedia Engineering Graduate School of Information Science and TechnologyOsaka UniversityOsakaJapan
  2. 2.Department of Systems and Social Informatics, Graduate School of Information ScienceNagoya UniversityNagoyaJapan

Personalised recommendations