Theoretical Frameworks for Improving the Computation of Skylines over Uncertain Data

Ma’aruf Mohammed Lawal, Hamidah Ibrahim, Nor Fazlida Mohd Sani and Razali Yaakob

Keywords: constrained skyline query, uncertain data, Indexing technique


Skyline query is preeminent for realizing solutions that support multi-criteria decision making, particularly for modern applications that often capture or generate large volume of high dimensional database. The essence of skyline query is to return a set of objects that is not dominated by any other objects. In this paper, we proposed frameworks namely; SQUiD, CSQUiD, and ASQUiD that deal with the computational problem associated with processing constrained skyline queries over uncertain data with high dimensionality. Although, solutions for processing such queries over uncertain data are available, but they are inefficient as they do not utilize the result of earlier computations. Since multiple constrained skyline queries might span over the same part of the database, this research work attempt to avoid unnecessary skyline computations of these queries by identifying the conditions specified in these queries.