- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Discrete Dynamics in Nature and Society
Volume 2013 (2013), Article ID 209672, 10 pages
Efficient Processing of Continuous Skyline Query over Smarter Traffic Data Stream for Cloud Computing
1State Key Laboratory of Rail Traffic Control and Safety, Beijing JiaoTong University, Beijing 100044, China
2School of Traffic and Transportation, Beijing JiaoTong University, Beijing 100044, China
3China National Tendering Center of Mach. & Elec. Equipment, Beijing 100142, China
4Chongqing Public Security Bureau, Chongqing 401147, China
Received 19 September 2013; Accepted 4 November 2013
Academic Editor: Huimin Niu
Copyright © 2013 Wang Hanning et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- M. Armbrust, A. Fox, R. Griffith, and M. Zaharia, “Above the Clouds: A Berkeley View of Cloud Computing,” Rep UCB/EECS-2009-28, UC, RAD Laboratory, Berkeley, Calif, USA, 2009.
- IBM, “The Case for Smarter Transportation,” Whitepaper, IBM-Institute for Business Value, 2010.
- B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom, “Models and issues in data stream systems,” in Proceedings of the 21st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS '02), pp. 1–16, New York, NY, USA, June 2002.
- H. Guo, W. Wang, W. Guo, X. Jiang, and H. Bubb, “Reliability analysis of pedestrian safety crossing in urban traffic environment,” Safety Science, vol. 50, no. 4, pp. 968–973, 2012.
- W. Wang, Y. Mao, J. Jin et al., “Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model,” International Journal of Computational Intelligence Systems, vol. 4, no. 3, pp. 297–305, 2011.
- S. Borzsonyi, D. Kossmamm, and K. Stocker, “The skyline operator,” in Proceedings of the 17th International Conference on Data Engineering, IEEE Computer Society, Washington, DC, USA, 2001.
- C. Jia, W. Xu, F. Wang, and H. Wang, “Track irregularity time series analysis and trend forecasting,” Discrete Dynamics in Nature and Society, vol. 2012, Article ID 387857, 15 pages, 2012.
- H. Wang, W. Xu, F. Wang, and C. A. Jia, “cloud-computing-based data placement strategy in high-speed railway,” Discrete Dynamics in Nature and Society, vol. 2012, Article ID 396387, 15 pages, 2012.
- J. I. A. Chaolong, X. U. Weixiang, W. E. I. Lili, et al., “Study of railway track irregularity standard deviation time series based on data mining and linear model,” Mathematical Problems in Engineering Volume, vol. 2013, Article ID 486738, 12 pages, 2013.
- C. K. -S. Leung, “Mining uncertain data,” Wiley Interdisciplinary Reviews, vol. 1, no. 4, pp. 316–329, 2011.
- G. Juve, E. Deelman, K. Vahi et al., “Scientific workflow applications on amazon EC2,” in Proceedings of the 5th IEEE International Conference on e-Science Workshops (e-science '09), pp. 59–66, Oxford, UK, December 2009.
- E. Wu, Y. Diao, and S. Rizvi, “High-performance complex event processing over streams,” in Proceddings of the ACM SIGMOD International Conference on Management of Data, pp. 407–418, June 2006.
- W. Zhang, X. Lin, Y. Zhang, W. Wang, and J. X. Yu, “Probabilistic skyline operator over sliding windows,” in Proceedings of the 25th IEEE International Conference on Data Engineering (ICDE '09), pp. 1060–1071, IEEE Computer Society, Shanghai, China, April 2009.
- J. Chomicki, P. Godfrey, J. Gryz, and D. Liang, “Skyline with presorting,” in Proceedings of the 19th International Conference on Data Ingineering, pp. 717–719, IEEE Computer Society, Bangalore, India, March 2003.
- D. Kossmann, F. Ramsak, and S. Rost, “Shooting stars in the sky: an online algorithm for Skyline ueries,” in Proceedings of the 28th International Conference on Very Large Data Bases (VLDB '02), pp. 275–286, Hong Kong, 2002.
- D. Papadias, Y. Tao, G. Fu, and B. Seeger, “An optimal and progressive algorithm for skyline queries,” in Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD '03), pp. 467–478, San Diego, Calif, USA, June 2003.
- K. L. Tan, P. K. Eng, and B. C. Ooi, “Efficient progressive Skyline computation,” in Proceedings of the 27th International Conference on Very Large Data Bases (VLDB '01), pp. 301–310, San Francisco, Calif, USA, 2001.
- P. Jian, J. Bin, L. Xuemin, et al., “Probabilistic Skylines on uncertain data,” in Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB '07), pp. 15–26, Vienna, Austria, 2007.
- M. E. Khalefa, M. F. Mokbel, and J. J. Levandoski, “Skyline query processing for uncertain data,” in Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops, (CIKM '10), pp. 1293–1296, Toronto, Canada, October 2010.
- Y. Tao and D. Papadias, “Maintaining sliding window skylines on data streams,” IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 3, pp. 377–391, 2006.
- X. Lin, Y. Yuan, W. Wang, and H. Lu, “Stabbing the sky: efficient skyline computation over sliding windows,” in Proceedings of the 21st International Conference on Data Engineering (ICDE '05), pp. 502–513, IEEE Computer Society, Tokyo, Japan, April 2005.
- W. Xiaowei, H. Jiuming, and J. Yan, “Probabilistic skyline computation on distributed uncertain data,” Journal of Frontiers of Computer Science and Technology, vol. 4, no. 10, pp. 951–961, 2010.
- X. Chuanfei, L. Shukuan, W. Lei, and Q. Jianzhong, “Complex event detection in probabilistic stream,” in Proceedings of the 12th International Asia Pacific Web Conference (APWeb '10), pp. 361–363, April 2010.
- X. Ding, X. Lian, L. Chen, and H. Jin, “Continuous monitoring of skylines over uncertain data streams,” Information Sciences, vol. 184, no. 1, pp. 196–214, 2012.
- S.-L. Sun, D.-B. Dai, Z.-H. Huang, Q.-X. Zhang, and L.-X. Zhou, “Algorithm on computing skyline over probabilistic data stream,” Acta Electronica Sinica, vol. 37, no. 2, pp. 285–293, 2009.
- J. B. Rocha-Junior, A. Vlachou, C. Doulkeridis, and K. Nørvåg, “Efficient execution plans for distributed skyline query processing,” in Proceedings of the 14th International Conference on Extending Database Technology: Advances in Database Technology (EDBT '11), pp. 271–282, Uppsala, Sweden, March 2011.
- Y. Yongtao and W. Yijie, “Towards estimating expected sizes of probabilistic Skylines,” Science China, vol. 53, no. 1, pp. 1–18, 2010.
- B. Cui, H. Lu, Q. Xu, L. Chen, Y. Dai, and Y. Zhou, “Parallel distributed processing of constrained skyline queries by filtering,” in Proceedings of the 24th International Conference on Data Engineering (ICDE '08), pp. 546–555, IEEE Computer Society, Cancun, Mexico, April 2008.
- X. Ding and H. Jin, “Efficient and progressive algorithms for distributed skyline queries over uncertain data,” in Proceeedings of the 30th IEEE International Conference on Distributed Computing Systems (ICDCS '10), pp. 149–158, Genoa, Italy, June 2010.