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Efficient Skyline Computation on Time-Interval Data Streams

유효시간 데이터 스트림에서의 스카이라인 질의 알고리즘

  • Received : 2011.11.08
  • Accepted : 2012.01.05
  • Published : 2012.01.31

Abstract

Multi-criteria result extraction is crucial in many scientific applications that support real-time stream processing, such as habitat research and disaster monitoring. Skyline evaluation is computational intensive especially over continuous time-interval data streams where each object has its own customized expiration time. In this work, we propose TI-Sky - a continuous skyline evaluation framework. To ensure correctness, the result space needs to be continuously maintained as new objects arrive and older objects expire. TI-Sky strikes a perfect balance between the costs of continuously maintaining the result space and the costs of computing the final skyline result from this space whenever a pull-based user query is received. Our key principle is to incrementally maintain a partially precomputed skyline result space - however doing so efficiently by working at a higher level of abstraction. TI-Sky's algorithms for insertion, deletion, purging and result retrieval exploit both layers of granularity. Our experimental study demonstrates the superiority of TI-Sky over existing techniques to handle a wide variety of data sets.

Keywords

Skyline;Time-interval Data Stream;Multi-Criteria Decision Support

References

  1. R. S. Barga, J. Goldstein, M. H. Ali, and M. Hong. "Consistent streaming through time: A vision for event stream processing", In CIDR, pages 363-374, 2007.
  2. S. Borzsonyi, D. Kossmann, and K. Stocker. "The skyline operator", In ICDE, pages 421-430, 2001.
  3. X. Lin, Y. Yuan,W.Wang, and H. Lu. "tabbing the sky: Efficient skyline computation over sliding windows", n ICDE, pages 502-513, 2005.
  4. M. Morse, J. Patel, and W. Grosky. "Efficient continuous skyline computation", Inf. Sci., pages 3411-3437, 2007.
  5. K. Mouratidis, S. Bakiras, and D. Papadias. "Continuous monitoring of top-k queries over sliding windows", In SIGMOD, pages 635-646, 2006.
  6. D. Papadias, Y. Tao, G. Fu, and B. Seeger. "An optimal and progressive algorithm for skyline queries", In SIGMOD, pages 467-478, 2003.
  7. U. Srivastava and J. Widom. "Flexible time management in data stream systems", In PODS, pages 263-274, 2004.
  8. Y. Tao and D. Papadias. "Maintaining sliding window skylines on data streams", TKDE (18:2), pages 377-391, 2006.
  9. Z. Zhang, R. Cheng, D. Papadias, and A. K. H. Tung. "Minimizing the communication cost for continuous skyline maintenance", In SIGMOD, pages 495-508, 2009.
  10. Shiming Zhang, N. Mamoulis, and D. W. Cheung. "Scalable skyline computation using object-based space partitioning", In Proc. SIGMOD, pp. 483-494, 2009.

Acknowledgement

Supported by : 한국연구재단