An efficient processing algorithm for ρ-dominant skyline query

In recent years, as an important operator for multi-decision making, skyline query has attracted much attention from the academia gradually, and a variety of skyline variants based on different dominance relationships have been proposed successively by the database researchers. In this paper, firstly, through making the analysis of practical applications' requirements, the ρ-dominance relationship based on the ratio of corresponding values between the tuples is defined, and then the concept of ρ-dominant skyline query based on the ρ-dominance relationship is proposed. Next, by making a detailed and in-depth analysis of ρ-dominance's basic properties, a novel algorithm, named Branch and Bound ρ-Dominant Skyline Algorithm (BBDS), is developed. The BBDS algorithm avoids visiting R-tree index too many times, which can improve the ρ-dominant skyline query implementation efficiency greatly. Finally, through a large number of simulation experiments, the semantic of the ρ-dominant skyline query is analyzed, and meanwhile the performance of BBDS algorithm is verified by the simulation experiments. The simulation experimental results show that ρ-dominant skyline query based on ρ-dominance relationship is a new extension and complement of the traditional skyline query semantic and the BBDS algorithm proposed in this paper is proved to be a highly effective algorithm for solving ρ-dominant skyline queries.