Nearest and farthest spatial skyline queries under multiplicative weighted Euclidean distances

作者：

Highlights：

• Suggest a new measure to determine the spatial skyline points considering distance and importance.

• Develop a mathematical study of the geometric properties of the weighted spatial skyline points.

• Propose a sequential and a parallel algorithm to obtain all or the top-k spatial skyline points.

• Algorithms are theoretically and experimentally analyzed and compared.

• The experimental results prove that the parallel algorithm is robust, efficient and faster than the sequential algorithm.

摘要

•Suggest a new measure to determine the spatial skyline points considering distance and importance.•Develop a mathematical study of the geometric properties of the weighted spatial skyline points.•Propose a sequential and a parallel algorithm to obtain all or the top-k spatial skyline points.•Algorithms are theoretically and experimentally analyzed and compared.•The experimental results prove that the parallel algorithm is robust, efficient and faster than the sequential algorithm.

论文关键词：Computer science,Decision-making support system,Nearest and farthest spatial skyline query,Weighted Euclidean distance,Graphics Processing Unit (GPU)

论文评审过程：Received 20 June 2019, Revised 19 November 2019, Accepted 27 November 2019, Available online 9 December 2019, Version of Record 24 February 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.105299