SKYLINE SETS QUERIES FOR INCOMPLETE DATA

With the increase of data volume, advanced queryoperators, such as skyline queries, are necessary in order to help users to handle the huge amount ofavailable data by identifying a set of interesting data objects. Skyline queries help us to filter unnecessary information efficiently and provide us cluesfor various decision making tasks. Most of the existing skyline algorithms cannot preserveindividual’s privacy and are not well suited for data with outliers and frequently updated data. Considering these issues, earlierwe have proposed skyline sets queries from databases where all dimensions are available for all data items and considered an efficient algorithm for computing convex skyline sets. In this paper, we use that idea for skyline sets queries for incomplete data and propose a method, namely, RBSSQ. RBSSQ method uses areplacement-based approach and is applicable to the databases having any n umber of missing dimensions in the database objects. We have conducted several experiments in terms of computational cost and found that our proposed method can efficiently compute skyline sets from data items with missing values.

[1]  Ben Y. Zhao,et al.  Parallelizing Skyline Queries for Scalable Distribution , 2006, EDBT.

[2]  Jan Chomicki,et al.  Skyline with presorting , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[3]  D. Walker,et al.  Patterns and Skeletons for Parallel and Distributed Computing , 2022 .

[4]  Mohammad Anisuzzaman Siddique,et al.  Algorithm for Computing Convex Skyline Objectsets on Numerical Databases , 2010, IEICE Trans. Inf. Syst..

[5]  Jonghyun Park,et al.  Parallel Skyline Computation on Multicore Architectures , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[6]  Donald Kossmann,et al.  Shooting Stars in the Sky: An Online Algorithm for Skyline Queries , 2002, VLDB.

[7]  Mohamed F. Mokbel,et al.  Skyline Query Processing for Incomplete Data , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[8]  Donald Kossmann,et al.  The Skyline operator , 2001, Proceedings 17th International Conference on Data Engineering.

[9]  Hua Lu,et al.  Parallel Distributed Processing of Constrained Skyline Queries by Filtering , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[10]  Yunjun Gao,et al.  Parallelizing Progressive Computation for Skyline Queries in Multi-disk Environment , 2006, DEXA.

[11]  Bernhard Seeger,et al.  An optimal and progressive algorithm for skyline queries , 2003, SIGMOD '03.

[12]  Beng Chin Ooi,et al.  Efficient Progressive Skyline Computation , 2001, VLDB.

[13]  Yasuhiko Morimoto,et al.  Agent-based anonymous skyline set computation in cloud databases , 2012, Int. J. Comput. Sci. Eng..

[14]  Mohammad Anisuzzaman Siddique,et al.  Skyline Sets Query and Its Extension to Spatio-temporal Databases , 2010, DNIS.

[15]  Yasuhiko Morimoto,et al.  Privacy Aware Parallel Computation of Skyline Sets Queries from Distributed Databases , 2011, 2011 Second International Conference on Networking and Computing.

[16]  Jarek Gryz,et al.  Maximal Vector Computation in Large Data Sets , 2005, VLDB.