Continuous k-dominant skyline computation on multidimensional data streams

Skyline queries are important due to their usefulness in many application domains. However, by increasing the number of attributes, the probability that a tuple dominates another one is reduced significantly. To attack this problem, k-dominant skylines have been proposed, relaxing the definition of domination. In this paper, we study the problem of continuous monitoring of k-dominant skylines, where multiple queries are running concurrently. The proposed method divides the space in pairs of attributes. For each pair, we compute skyline tuples and we exploit them to eliminate candidates tuples of the queries and we combine the partial results. The proposed scheme uses only simple domination checks and it is applicable to the streaming case as well as to ad-hoc insertions and deletions. Experiments, based on different data distributions, show the efficiency of the proposed scheme in comparison to existing methods. Categories and Subject Descriptors H.2.4 [Database Management]: Systems--...

• Type: Journal
• Year: 2008
• Where: SAC
• Authors: Maria Kontaki, Apostolos N. Papadopoulos, Yannis Manolopoulos
• Keywords: Applied Computing, K-dominant Skylines, SAC 2008, Simple Domination Checks, Tuples