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Feedback Based Continuous Skyline Queries Over a Distributed Framework

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Advances in Databases and Information Systems (ADBIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9282))

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Abstract

Continuous skyline query processing is becoming wide spread. Most of the work done in this field is focused to process skyline queries on a single machine. Our focus is to process continuous skyline queries over data streams, where data is arriving at server in the form of continuous updates from multiple distributed input sources. A single machine solution to run continuous skyline queries over streaming data is not very scalable. Moreover, streaming data arriving from multiple sources can overwhelm server’s computing power, specially if the skyline queries are involved to compute high quality multidimensional skyline points. We propose a three layer solution to compute continuous skyline points. A bottom layer in our approach sends the local skyline points to the middle layer, which after receiving feedback from the server filters the false-positives, and produces the semi-global skyline points to be sent to the server for global skyline. Our approach being scalable distributes the workloads across the network on multiple machines and reduces the number of unnecessary data points to be sent to the server, allowing it to produce qualitative skyline points.

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References

  1. Lu, H., Zhou, Y., Haustad, J.: Continuous skyline monitoring over distributed data streams. In: Gertz, M., Ludäscher, B. (eds.) SSDBM 2010. LNCS, vol. 6187, pp. 565–583. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  2. Borzsony, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proceedings of the 17th International Conference on Data Engineering, pp. 421–430. IEEE (2001)

    Google Scholar 

  3. Endres, M., Roocks, P., Kießling, W.: Scalagon: an efficient skyline algorithm for all seasons. In: Renz, M., Shahabi, C., Zhou, X., Chemma, M.A. (eds.) DASFAA 2015. LNCS, vol. 9050, pp. 292–308. Springer, Heidelberg (2015)

    Google Scholar 

  4. Liknes, S., Vlachou, A., Doulkeridis, C., Nørvåg, K.: APSkyline: improved skyline computation for multicore architectures. In: Bhowmick, S.S., Dyreson, C.E., Jensen, C.S., Lee, M.L., Muliantara, A., Thalheim, B. (eds.) DASFAA 2014, Part I. LNCS, vol. 8421, pp. 312–326. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  5. Endres, M., Kießling, W.: High parallel skyline computation over low-cardinality domains. In: Manolopoulos, Y., Trajcevski, G., Kon-Popovska, M. (eds.) ADBIS 2014. LNCS, vol. 8716, pp. 97–111. Springer, Heidelberg (2014)

    Google Scholar 

  6. Chester, S., Sidlauskas, D., Assent, I.: Bøgh, K.S.: Scalable parallelization of skyline computation for multi-core processors (2015)

    Google Scholar 

  7. Chomicki, J., Godfrey, P., Gryz, J., Liang, D.: Skyline with presorting. In: ICDE, vol. 3, pp. 717–719 (2003)

    Google Scholar 

  8. Tan, K.L., Eng, P.K., Ooi, B.C., et al.: Efficient progressive skyline computation. In: VLDB, vol. 1, pp. 301–310 (2001)

    Google Scholar 

  9. Kossmann, D., Ramsak, F., Rost, S.: Shooting stars in the sky: an online algorithm for skyline queries. In: Proceedings of the 28th International Conference on Very Large Data Bases, VLDB Endowment, pp. 275–286 (2002)

    Google Scholar 

  10. Papadias, D., Tao, Y., Fu, G., Seeger, B.: An optimal and progressive algorithm for skyline queries. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 467–478. ACM (2003)

    Google Scholar 

  11. Yiu, M.L., Mamoulis, N.: Efficient processing of top-k dominating queries on multi-dimensional data. In: Proceedings of the 33rd International Conference on Very Large Data Bases, VLDB Endowment, pp. 483–494 (2007)

    Google Scholar 

  12. Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. ACM Trans. Database Syst. (TODS) 30(1), 41–82 (2005)

    Article  Google Scholar 

  13. Dellis, E., Seeger, B.: Efficient computation of reverse skyline queries. In: Proceedings of the 33rd International Conference on Very Large Data Bases, VLDB Endowment, pp. 291–302 (2007)

    Google Scholar 

  14. Morse, M., Patel, J.M., Jagadish, H.: Efficient skyline computation over low-cardinality domains. In: Proceedings of the 33rd International Conference on Very Large Data Bases, VLDB Endowment, pp. 267–278 (2007)

    Google Scholar 

  15. Lee, K.C., Zheng, B., Li, H., Lee, W.C.: Approaching the skyline in Z order. In: Proceedings of the 33rd International Conference on Very Large Data Bases, VLDB Endowment, pp. 279–290 (2007)

    Google Scholar 

  16. Pei, J., Jiang, B., Lin, X., Yuan, Y.: Probabilistic skylines on uncertain data. In: Proceedings of the 33rd International Conference on Very Large Data Bases, VLDB Endowment, pp. 15–26 (2007)

    Google Scholar 

  17. Balke, W.-T., Güntzer, U., Zheng, J.X.: Efficient distributed skylining for web information systems. In: Bertino, E., Christodoulakis, S., Plexousakis, D., Christophides, V., Koubarakis, M., Böhm, K. (eds.) EDBT 2004. LNCS, vol. 2992, pp. 256–273. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  18. Wu, P., Zhang, C., Feng, Y., Zhao, B.Y., Agrawal, D.P., El Abbadi, A.: Parallelizing skyline queries for scalable distribution. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 112–130. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  19. Huang, Z., Jensen, C.S., Lu, H., Ooi, B.C.: Skyline queries against mobile lightweight devices in manets. In: Proceedings of the 22nd International Conference on Data Engineering, ICDE 2006 p. 66. IEEE (2006)

    Google Scholar 

  20. Zhu, L., Tao, Y., Zhou, S.: Distributed skyline retrieval with low bandwidth consumption. IEEE Trans. Knowl. Data Eng. 21(3), 384–400 (2009)

    Article  Google Scholar 

  21. Huang, Z., Lu, H., Ooi, B.C., Tung, A.: Continuous skyline queries for moving objects. IEEE Trans. Knowl. Data Eng. 18(12), 1645–1658 (2006)

    Article  Google Scholar 

  22. Lin, X., Yuan, Y., Wang, W., Lu, H.: Stabbing the sky: Efficient skyline computation over sliding windows. In: Proceedings 21st International Conference on Data Engineering, ICDE 2005, pp. 502–513. IEEE (2005)

    Google Scholar 

  23. Tao, Y., Papadias, D.: Maintaining sliding window skylines on data streams. IEEE Trans. Knowl. Data Eng. 18(3), 377–391 (2006)

    Article  Google Scholar 

  24. Wu, P., Agrawal, D., Egecioglu, O., El Abbadi, A.: Deltasky: Optimal maintenance of skyline deletions without exclusive dominance region generation. In: IEEE 23rd International Conference on Data Engineering, ICDE 2007, pp. 486–495. IEEE (2007)

    Google Scholar 

  25. Zhang, Z., Cheng, R., Papadias, D., Tung, A.K.: Minimizing the communication cost for continuous skyline maintenance. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, pp. 495–508. ACM (2009)

    Google Scholar 

  26. Mouratidis, K., Papadias, D., Hadjieleftheriou, M.: Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pp. 634–645. ACM (2005)

    Google Scholar 

  27. Mullesgaard, K., Pedersen, J.L., Lu, H., Zhou, Y.: Efficient skyline computation in mapreduce. In: 17th International Conference on Extending Database Technology (EDBT), pp. 37–48 (2014)

    Google Scholar 

  28. Lu, H., Zhou, Y., Haustad, J.: Efficient and scalable continuous skyline monitoring in two-tier streaming settings. Inf. Syst. 38(1), 68–81 (2013)

    Article  Google Scholar 

  29. Cui, B., Lu, H., Xu, Q., Chen, L., Dai, Y., Zhou, Y.: Parallel distributed processing of constrained skyline queries by filtering. In: IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 546–555. IEEE (2008)

    Google Scholar 

  30. NASDAQ. http://www.infochimps.com/. Accessed 03 December 2014

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Correspondence to Ahmed Khan Leghari .

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Leghari, A.K., Cao, J., Zhou, Y. (2015). Feedback Based Continuous Skyline Queries Over a Distributed Framework. In: Tadeusz, M., Valduriez, P., Bellatreche, L. (eds) Advances in Databases and Information Systems. ADBIS 2015. Lecture Notes in Computer Science(), vol 9282. Springer, Cham. https://doi.org/10.1007/978-3-319-23135-8_20

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  • DOI: https://doi.org/10.1007/978-3-319-23135-8_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23134-1

  • Online ISBN: 978-3-319-23135-8

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