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Continuous Probabilistic Subspace Skyline Query Processing Using Grid Projections

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Abstract

As an important type of multidimensional preference query, the skyline query can find a superset of optimal results when there is no given linear function to combine values for all attributes of interest. Its processing has been extensively investigated in the past. While most skyline query processing algorithms are designed based on the assumption that query processing is done for all attributes in a static dataset with deterministic attribute values, some advanced work has been done recently to remove part of such a strong assumption in order to process skyline queries for real-life applications, namely, to deal with data with multi-valued attributes (known as data uncertainty), to support skyline queries in a subspace which is a subset of attributes selected by the user, and to support continuous queries on streaming data. Naturally, there are many application scenarios where these three complex issues must be considered together. In this paper, we tackle the problem of probabilistic subspace skyline query processing over sliding windows on uncertain data streams. That is, to retrieve all objects from the most recent window of streaming data in a user-selected subspace with a skyline probability no smaller than a given threshold. Based on the subtle relationship between the full space and an arbitrary subspace, a novel approach using a regular grid indexing structure is developed for this problem. An extensive empirical study under various settings is conducted to show the effectiveness and efficiency of our PSS algorithm.

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Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, 215006, China

    Lei Zhao & Xiaofang Zhou

  2. Open System & Storage Interoperability Test Laboratory, IBM, Wuxi, 214000, China

    Yan-Yan Yang

  3. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, 4072, Australia

    Xiaofang Zhou

Authors
  1. Lei Zhao
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  2. Yan-Yan Yang
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  3. Xiaofang Zhou
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Corresponding author

Correspondence to Lei Zhao.

Additional information

This work is supported by the National Natural Science Foundation of China under Grant Nos. 61073061, 61003044, 61303019, and the Natural Science Foundation of Colleges and Universities of Jiangsu Province of China under Grant No. 12KJB520017.

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Zhao, L., Yang, YY. & Zhou, X. Continuous Probabilistic Subspace Skyline Query Processing Using Grid Projections. J. Comput. Sci. Technol. 29, 332–344 (2014). https://doi.org/10.1007/s11390-014-1434-9

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  • DOI: https://doi.org/10.1007/s11390-014-1434-9

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