Dynamic Skyline Queries in Large Graphs

Abstract. Given a set of query points, a dynamic skyline query reports all data points that are not dominated by other data points according to the distances between data points and query points. In this paper, we study dynamic skyline queries in a large graph (DSG-query for short). Although dynamic skylines have been studied in Euclidean space [16], road network [6], and metric space [4, 7], there is no previous work on dynamic skylines over large graphs. We employ a filter-and-refine framework to speed up the query processing that can answer DSG-query efficiently. We propose a novel pruning rule based on graph properties to derive the candidates for DSG-query, that are guaranteed not to introduce false negatives. In the refinement step, with a carefully-designed index structure, we compute short path distances between vertices in O(H), where H is the number of maximal hops between any two vertices. Extensive experiments demonstrate that our methods outperform existing algorithms by orders of magnitude.