Real-Time Skyline Computation on Data Streams

Skyline processing has received considerable attention in the last decade, in particular when filtering the most preferred objects from a multi-dimensional set on contradictory criteria. Nowadays, an enormous number of applications require the analysis of time evolving data and therefore the study of continuous query processing has recently attracted the interest of researchers all over the world. In this paper, we propose a novel algorithm called SLS for evaluating Skyline queries with low-cardinality domains on data streams, and empirically demonstrate the advantage of this algorithm on artificial and real data.