New fragmentation and allocation technique for distributed database system

Abstract

An efficient way of improving pelformance of a database management system is distributed processing. Distribution of data involves fragmentation, replication and allocation process. Previous research works provided fragmentation solution based on empirical data about the type and frequency of the queries. These solutions are not suitable at th~ .initial stage of a distributed database. In this thesis we have presented a fragmentation technique namely MCRUD Matrix based Fragmentation (MMF) that can be applied at the initial stage as well as in later stages of a distributed database system for partitioning the relations. Instead of using empirical data, we have developed the matrix namely Modified Create, Read, Update and Delete to make fragmentation decisions properly. The main 'concept of MMF is finding the precedence of attributes to increase data locality. We have named it Attribute Locality Precedence (ALP). The r~lations have been fragmented considering the highest ALP value an10ng the attributes Allocation of fragments is done simultaneously in our technique. So using MMF, no additional complexity is added for allocating the fragments to the sites of a distributed database as fragmentation is synchronized with allocation. Performance of a DDBMS can be improved significantly by avoiding frequent remote access and high data transfer among the sites. Result shows that the proposed technique can solve initial fragmentation problem of distributed system properly.