A Hybrid Approach for Efficient Database Fragmentation in Distributed Systems

Muhammad Usman Younus; Muhammad Shoaib; Kalsoom Safdar; Abdul Basit Dogar

Authors

Muhammad Usman Younus Ecole Doctorale Matheematiques, Informatique, Telecommunication de Toulouse, University of Toulouse (III), Paul Sabatier, Toulouse, France
Muhammad Shoaib Department of Computer Science & IT, University of Jhang, Jhang, Pakistan
Kalsoom Safdar Faculty of Electronic Engineering and Technology, University Malaysia Perlis, 02600 Arau, Perlis, Malaysia
Abdul Basit Dogar Department of Informatics and Systems, School of Systems and Technology, University of Management and Technology Lahore, Pakistan

Keywords:

Horizontal Fragmentation, Distributed Database, Query Optimisation, Attribute Locality, MCRUD

Abstract

Distributed Database Management Systems (DDBMSs) require effective data allocation techniques to ensure scalability, availability, and performance in distributed systems of geographically decentralized nodes. The traditional fragmentation procedures fail to consider the dynamic access frequency and attribute locality, leading to increased query costs and storage overhead. In this paper, we develop a new Derived Horizontal Fragmentation method, called MCRUD, that aims to optimise fragment placement by incorporating attribute locality and access frequency into the fragmentation process. The proposed model was tested and applied in a simulated distributed database environment, and its performance was compared with that of conventional horizontal fragmentation techniques. The metrics used to measure performance included query response time, storage overhead, data transfer rate, and computation time. Experimental findings show that the MCRUD method significantly improves system performance by reducing data retrieval time and data storage redundancy, without affecting data consistency or availability. The results show that the proposed fragmentation strategy improves the scalability and load balancing in the distributed database systems. MCRUD model offers a powerful data distribution mechanism that can be applied to a large-scale distributed environment and optimised to adapt to workload and modify database optimisation in future studies.

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