Subspace global skyline query processing

Global skyline, as an important variant of skyline, has been widely applied in multiple criteria decision making, business planning and data mining, while there are no previous studies on the global skyline query in the subspace. Hence in this paper we propose subspace global skyline (SGS) query, which is concerned about global skyline in ad hoc subspace. Firstly, we propose an appropriate index structure RB-tree to rapidly find the initial scan positions of query. Secondly, by making analysis of basic properties of SGS, we propose a single SGS algorithm based on RB-tree (SSRB) to compute SGS points. Then an optimized single SGS algorithm based on RB-tree (OSSRB) is proposed, which can reduce the scan space and improve the computation efficiency in contrast to SSRB. Next, by sharing the scan space of different queries, a multiple SGS algorithm based on RB-tree (MSRB) is proposed to compute multiple SGS (MSGS). Finally, the performances of our proposed algorithms are verified through a large number of simulation experiments.