Clustered Approach to Dynamic Data Allocation in Distributed Database Systems

Main Article Content

Raju Kumar
Neena Gupta

Abstract

Distributed database is very much popular in organizations which are distributed and operating from multiple geographic locations. The two important issues to improve the performance of distributed database systems (DDS) are - grouping of different sites into clusters, and dynamic reallocation of data fragment to these clusters. Clustering network sites and data allocation are still open research problems as their optimal solution is NP-hard. The prime contribution in this field is to develop a near optimal solution. In this paper a new algorithm is proposed for clustering distributed database sites based on the distance between sites to minimise the number of communications and network overhead between sites. Moreover, a Clustered Approach to Dynamic Data Allocation (CADDA) algorithm is proposed to dynamically reallocate data fragments to clusters in redundant and non-redundant distributed database system to reduce the remote data accesses and network overhead. The proposed approach is implemented on a sample distributed database system and compared with other cluster and non-cluster based data allocation algorithms. The comparison results show that proposed approach efficiency is better and it improves the overall performance of the distributed database system.

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Author Biographies

Raju Kumar, Research Scholar, Department of Computer Science, Gurukul Kangri Vishwavidyalaya, Haridwar, India

Research Scholar, Department of Computer Science, Gurukul Kangri Vishwavidyalaya, Haridwar, India

Neena Gupta, Assistant Professor, Department of Computer Science, Kanya Gurukul Mahavidyalaya Dehradun (Second Campus of Gurukul Kangri Vishwavidyalaya, Haridwar), India

Assistant Professor, Department of Computer Science, Kanya Gurukul Mahavidyalaya Dehradun (Second Campus of Gurukul Kangri Vishwavidyalaya, Haridwar), India

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