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


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.


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


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Supported by : 한국연구재단