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Issue No.01 - January-March (2010 vol.3)
pp: 16-29
Qi Yu , Rochester Institute of Technology, Rochester
Athman Bouguettaya , CSIRO, ICT Center, Acton ACT, Australia
ABSTRACT
The performance of a service provider may fluctuate due to the dynamic service environment. Thus, the quality of service actually delivered by a service provider is inherently uncertain. Existing service optimization approaches usually assume that the quality of service does not change over time. Moreover, most of these approaches rely on computing a predefined objective function. When multiple quality criteria are considered, users are required to express their preference over different (and sometimes conflicting) quality attributes as numeric weights. This is rather a demanding task and an imprecise specification of the weights could miss user-desired services. We present a novel concept, called p-dominant service skyline. A provider S belongs to the p-dominant skyline if the chance that S is dominated by any other provider is less than p. Computing the p-dominant skyline provides an integrated solution to tackle the above two issues simultaneously. We present a p-R-tree indexing structure and a dual-pruning scheme to efficiently compute the p-dominant skyline. We assess the efficiency of the proposed algorithm with an analytical study and extensive experiments.
INDEX TERMS
Quality of service, service optimization, service selection, skyline analysis, uncertainty.
CITATION
Qi Yu, Athman Bouguettaya, "Computing Service Skyline from Uncertain QoWS", IEEE Transactions on Services Computing, vol.3, no. 1, pp. 16-29, January-March 2010, doi:10.1109/TSC.2010.7
REFERENCES
[1] F. Barbon, P. Traverso, M. Pistore, and M. Trainotti, "Run-Time Monitoring of Instances and Classes of Web Service Compositions," Proc. Int'l Conf. Web Services (ICWS), 2006.
[2] S. Borzsonyi, D. Kossmann, and K. Stocker, "The Skyline Operator," Proc. Int'l Conf. Data Eng. (ICDE), 2001.
[3] C.Y. Chan, H.V. Jagadish, K.L. Tan, A.K.H. Tung, and Z. Zhang, "Finding k-Dominant Skylines in High Dimensional Space," Proc. SIGMOD, 2006.
[4] R. Cheng, D.V. Kalashnikov, and S. Prabhakar, "Evaluating Probabilistic Queries over Imprecise Data," Proc. SIGMOD, 2003.
[5] R. Cheng, Y. Xia, S. Prabhakar, R. Shah, and J.S. Vitter, "Efficient Indexing Methods for Probabilistic Threshold Queries over Uncertain Data," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2004.
[6] J. Chomicki, P. Godfrey, J. Gryz, and D. Liang, "Skyline with Presorting," Proc. Int'l Conf. Data Eng. (ICDE), 2003.
[7] M. Comuzzi and B. Pernici, "A Framework for QoS-Based Web Service Contracting," ACM Trans. Web, vol. 3, no. 3, pp. 1-52, 2009.
[8] P. Godfrey, R. Shipley, and J. Gryz, "Maximal Vector Computation in Large Data Sets," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2005.
[9] A. Guttman, "R-Trees: A Dynamic Index Structure for Spatial Searching," Readings in Database Systems, pp. 599-609, Morgan Kaufmann, 1988.
[10] R. Jurca, B. Faltings, and W. Binder, "Reliable QoS Monitoring Based on Client Feedback," Proc. Conf. World Wide Web (WWW), 2007.
[11] D. Kossmann, F. Ramsak, and S. Rost, "Shooting Stars in the Sky: An Online Algorithm for Skyline Queries," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2002.
[12] H.P. Kriegel, P. Kunath, M. Pfeifle, and M. Renz, "Probabilistic Similarity Join on Uncertain Data," Proc. Int'l Conf. Database Systems for Advanced Applications (DASFAA), 2006.
[13] H.T. Kung, F. Luccio, and F.P. Preparata, "On Finding the Maxima of a Set of Vectors," J. ACM, vol. 22, no. 4, pp. 469-476, 1975.
[14] D. Papadias, Y. Tao, G. Fu, and B. Seeger, "An Optimal and Progressive Algorithm for Skyline Queries," Proc. SIGMOD, 2003.
[15] J. Pei, B. Jiang, X. Lin, and Y. Yuan, "Probabilistic Skylines on Uncertain Data," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2007.
[16] F.P. Preparata and M.I. Shamos, Computational Geometry: An Introduction. Springer-Verlag, 1985.
[17] A.D. Sarma, O. Benjelloun, A.Y. Halevy, and J. Widom, "Working Models for Uncertain Data," Proc. Int'l Conf. Data Eng. (ICDE), 2006.
[18] U. Srivastava, J. Widom, K. Munagala, and R. Motwani, "Query Optimization over Web Services," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2006.
[19] K.-L. Tan, P.-K. Eng, and B.C. Ooi, "Efficient Progressive Skyline Computation," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2001.
[20] Y. Tao, R. Cheng, X. Xiao, W.K. Ngai, B. Kao, and S. Prabhakar, "Indexing Multi-Dimensional Uncertain Data with Arbitrary Probability Density Functions," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2005.
[21] T. Yu, Y. Zhang, and K.J. Lin, "Efficient Algorithms for Web Services Selection with End-to-End QoS Constraints," ACM Trans. Web, vol. 1, no. 1, 2007.
[22] L. Zeng, B. Benatallah, M. Dumas, J. Kalagnanam, and Q. Sheng, "Quality-Driven Web Service Composition," Proc. Conf. World Wide Web (WWW), 2003.
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