Abstract
Skyline query processing reveals a set of preferable results based on the competitiveness of many criteria among all data objects. This is a very useful query for multi-attribute decision making. Moreover, monitoring and tracing skyline over time-series data are also important not only for real-time applications (e.g., environmental monitoring) but also historical time-series analysis (e.g., sports archives, historical stock data). In these applications, considering consecutive snapshots, a large fraction of the fixed number of observing objects (e.g., weather stations) can change their values resulting to the possibility of complete change in the previous skyline. Without any technique, computing skyline from a scratch is unavoidable and can be outperformed some traditional skyline update methods. In this paper, we propose an efficient method to compute skyline sets over data update streams. Our proposed method uses bounding boxes to summarize consecutive data updates of each data object. This technique enables the pruning capability to identify a smaller set of candidates in skyline computation resulting in faster total computation time. We conduct some experiments through both synthetic and real-life datasets. The results explicitly show that our proposed method significantly runs faster than the baseline in various parameter studies.
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References
Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: ICDE, pp. 421–430 (2001)
Cheema, M.A., Lin, X., Zhang, W., Zhang, Y.: A safe zone based approach for monitoring moving skyline queries. In: EDBT, pp. 275–286, ACM (2013)
Dellis, E., Seeger, B.: Efficient computation of reverse skyline queries. In: VLDB, pp. 291–302, VLDB Endowment (2007)
Ding, X., Lian, X., Chen, L., Jin, H.: Continuous monitoring of skylines over uncertain data streams. Inf. Sci. 184(1), 196–214 (2012)
Hose, K., Vlachou, A.: A survey of skyline processing in highly distributed environments. VLDB J. 21(3), 359–384 (2012)
Hsueh, Y.-L., Zimmermann, R., Ku, W.-S.: Efficient updates for continuous skyline computations. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds.) DEXA 2008. LNCS, vol. 5181, pp. 419–433. Springer, Heidelberg (2008)
Huang, Z., Lu, H., Ooi, B.C., Tung, A.: Continuous skyline queries for moving objects. IEEE TKDE 18(12), 1645–1658 (2006)
Jiang, B., Pei, J.: Online interval skyline queries on time series. In: ICDE, pp. 1036–1047, IEEE Computer Society, Washington, DC, USA (2009)
Lee, M.-W., Hwang, S.-W.: Continuous skylining on volatile moving data. In: ICDE, pp. 1568–1575 (2009)
Lee, Y.W., Lee, K.Y., Kim, M.H.: Efficient processing of multiple continuous skyline queries over a data stream. Inf. Sci. 221, 316–337 (2013)
Morse, M., Patel, J.M., Grosky, W.I.: Efficient continuous skyline computation. Inf. Sci. 177(17), 3411–3437 (2007)
Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. TODS 30(1), 41–82 (2005)
Papapetrou, O., Garofalakis, M.: Continuous fragmented skylines over distributed streams. In: ICDE, pp. 124–135 (2014)
Sultana, A., Hassan, N., Li, C., Yang, J., Yu, C.: Incremental discovery of prominent situational facts. In: ICDE, pp. 112–123, IEEE (2014)
Sun, S., Huang, Z., Zhong, H., Dai, D., Liu, H., Li, J.: Efficient monitoring of skyline queries over distributed data streams. Knowl. Inf. Syst. 25(3), 575–606 (2010)
Tao, Y., Xiao, X., Pei, J.: Subsky: efficient computation of skylines in subspaces. In: ICDE, pp. 65–65, IEEE (2006)
Tian, L., Wang, L., Li, A.-P., Zou, P., Jia, Y.: Continuous skyline tracking on update data streams. In: Chang, K.C.-C., Wang, W., Chen, L., Ellis, C.A., Hsu, C.-H., Tsoi, A.C., Wang, H. (eds.) APWeb/WAIM 2007. LNCS, vol. 4537, pp. 192–197. Springer, Heidelberg (2007)
Xin, J., Wang, G., Chen, L., Zhang, X., Wang, Z.: Continuously maintaining sliding window skylines in a sensor network. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 509–521. Springer, Heidelberg (2007)
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Udomlamlert, K., Hara, T., Nishio, S. (2015). Candidate Pruning Technique for Skyline Computation Over Frequent Update Streams. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds) Database and Expert Systems Applications. Globe DEXA 2015 2015. Lecture Notes in Computer Science(), vol 9262. Springer, Cham. https://doi.org/10.1007/978-3-319-22852-5_9
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