Abstract
The skyline query is an efficient data analysis tool for multi-criteria decision making that has received significant attention in the database community. As multi-core architectures have gone mainstream, we present a new parallel skyline query algorithm that can be applied to multi-core and multiprocessor systems, to progressively return skyline points as they are identified efficiently. In this paper, we proposed a parallel skyline algorithm which can eliminate redundant computations and improve parallelism of the skyline query. Experimental results show that our algorithm successfully exploits the features of multiple cores to improve the performance of skyline computation for large high-dimensional datasets.
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