Publication Type:

Conference Paper

Source:

2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE, Chennai, India (2016)

ISBN:

9781509006120

URL:

https://ieeexplore.ieee.org/document/7919539

Keywords:

clustered fragments, Clustering, Clustering algorithms, clustering technique, Computer science, data semantics, Distributed database, Distributed database systems, distributed databases, distributed query processing, empirical data, fragmentation, horizontal fragmentation method, initial database design, pattern clustering, Performance improvements, Prototypes, query patterns, Query processing, Resource management, Semantics, time improvements

Abstract:

The need for distributed database systems increases day by day due to the need of running organizations from different locations. The efficiency and performance of distributed query processing depends on fragmentation and allocation method used. Usually, the fragmentation solutions are based on empirical data and analyzing query patterns. These methods can only be applied for the existing distributed databases and cannot be applied during initial database design. Also, most of the existing methods does not consider the semantics or relationships of the data being fragmented. Better fragments can be produced if data semantics are considered during fragmentation. Related data can be obtained from dataset using clustering technique. In this paper we propose a new horizontal fragmentation scheme based on clustering. Performance and time improvements are found while performing with clustered fragments.

Cite this Research Publication

Raji Ramachandran, Nair, D. P., and Jasmi, J., “A Horizontal Fragmentation Method Based on Data Semantics”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Chennai, India, 2016.