Continuous Road Network-Based Skyline Query for Moving Objects

Abstract

With the development of location-based services and smart terminals, skyline query technique has been used widely in intelligent transportation systems. In skyline queries, the areas and keywords queried by users have a great impact on the quality of the query results and users may only be interested in the closer results of the skyline query. However, current approaches for the continuous skyline query limit the area of the skyline query to a specific area in the road network, which leads to that many useful query results cannot be retrieved. To this end, an innovative continuous skyline query approach in city range is proposed in this paper, where a multi-scale area divisions of the urban road network are provided to find the optimize query scale and area. In our approach, first, the dominant area of each intersection node in the road network is established based on the Voronoi. Then, all Points of Interest (POIs) are divided into the dominant area of each intersection node. After that, the intersection node aggregation algorithm (INAA), link remolding algorithm (LMA) and link fitting algorithm (LFA) are proposed to reduce the number of intersection nodes in the road network, so as to increase the dominant area of the remaining intersection nodes and the number of POIs in these nodes. Finally, a better query scale by considering the efficiency and quality of the query is given through the studies.