Supporting efficient distributed skyline computation using skyline views

Skyline queries return a set of objects, or a skyline, that are not dominated by any other objects. While providing users with an intuitive query formulation, the skyline queries may incur too many results, especially, for high dimensional data. To tackle this problem, subspace skyline queries, which deals with a subset of dimensions, have been recently studied. To identify interesting skylines, users can iteratively refine multiple relevant subspaces for skyline queries. Existing work focuses primarily on supporting efficient subspace skyline computation in centralized databases. In clear contrast, this paper aims to address subspace skyline computation in distributed environments such as the Web. Toward this goal, we make use of pre-computed subspace skylines as views in databases, called skyline views. Specifically, we propose distributed subspace skyline computation which minimizes the total access cost by leveraging the skyline views. Our experimental results validate that our proposed algorithms significantly outperform state-of-the-art algorithms in extensive synthetic datasets.