Skyline cube (
SC) is an extension of data cube, where the
skyline operation is used to
aggregate each cell of tuples with the same values of
dimension attributes. To make
SC more effective decision making tool,
range query regarding
SC is potentially promising. This paper discusses the storage structure of
SC and
range query processing system.
R-tree based storage structure is dedicated to multi-dimensional index which associates values of
dimension attributes with the corresponding results of extended
skyline operation. The sequential processing system and the parallel processing system are built upon
R-tree based storage structure to answer
range queries. Experimental results show that
R-tree based storage structure is allowable, because its storage size is at most 3 times as that of
materialized view. Also, both of the sequential processing system and the parallel processing system are superior to the
materialized view system in processing
range queries. Especially, the parallel processing system takes below 20% times as that of the
materizalized view system, even in the case of
range query including anti-correlation
skyline attributes which entail heavy burdens.
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