Efficient Index-Based Approaches for Skyline Queries in Location-Based Applications

Enriching many location-based applications, various new skyline queries are proposed and formulated based on the notion of locational dominance, which extends conventional one by taking objects' nearness to query positions into account additional to objects' nonspatial attributes. To answer a representative class of skyline queries for location-based applications efficiently, this paper presents two index-based approaches, namely, augmented R-tree and dominance diagram. Augmented R-tree extends R-tree by including aggregated nonspatial attributes in index nodes to enable dominance checks during index traversal. Dominance diagram is a solution-based approach, by which each object is associated with a precomputed nondominance scope wherein query points should have the corresponding object not locationally dominated by any other. Dominance diagram enables skyline queries to be evaluated via parallel and independent comparisons between nondominance scopes and query points, providing very high search efficiency. The performance of these two approaches is evaluated via empirical studies, in comparison with other possible approaches.