Dynamic Skyline Queries in Large Graphs

Lei Zou, Lei Chen, M. Tamer Özsu, Dongyan Zhao

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 d ynamic s kyline queries in a large g raph (DSG-query for short). Although dynamic skylines have been studied in Euclidean space [14], road network [5], and metric space [3,6], 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.