Progressive skylining over web-accessible databases

  • Authors:

  • Eric Lo;Kevin Y. Yip;King-Ip Lin;David W. Cheung

  • Affiliations:

  • Department of Computer Science, ETH Zurich, Zurich, Switzerland and University of Hong Kong;Department of Computer Science, Yale University, United States;Division of Computer Seience, The University of Memphis, United States;Department of Computer Science, The University of Hong Kong, Hong Kong

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Skyline queries return a set of interesting data points that are not dominated on all dimensions by any other point. Most of the existing algorithms focus on skyline computation in centralized databases, and some of them can progressively return skyline points upon identification rather than all in a batch. Processing skyline queries over the Web is a more challenging task because in many Web applications, the target attributes are stored at different sites and can only be accessed through restricted external interfaces. In this paper, we develop PDS (progressive distributed skylining), a progressive algorithm that evaluates skyline queries efficiently in this setting. The algorithm is also able to estimate the percentage of skyline objects already retrieved, which is useful for users to monitor the progress of long running skyline queries. Our performance study shows that PDS is efficient and robust to different data distributions and achieves its progressive goal with a minimal overhead.