Location-based skyline query processing technology in road networks

Location-based skyline queries in road networks can quickly return the desired data to the user from a large amount of data according to the user's needs and location. However, there is no effective mechanism for calculating the road network distance and judging the dominant relationship between data points in the existing skyline queries algorithms in road networks. In this paper, we propose improved dynamic skyline queries in road networks, which can quickly compute all skyline points in road networks. Firstly, this paper proposes a GD-tree index, which efficiently stores the location information of the target tuple in the road network and speeds up the calculation of the road network distance. In addition, the concept of the optimal scan end point is proposed to reduce the calculation cost. The histogram of frequency statistical is proposed for the non-spatial dimension, and the nearest and farthest distance is calculated for the spatial dimension to select the optimal scan end point. Finally, extensive experiments in real road network datasets demonstrate the efficiency of the proposed algorithm.