Dynamic Data Allocation Methods in Distributed Database System

By Gope, Dejan Chandra | American Academic & Scholarly Research Journal, November 2012 | Go to article overview

Dynamic Data Allocation Methods in Distributed Database System


Gope, Dejan Chandra, American Academic & Scholarly Research Journal


ABSTRACT: Allocation of data or fragments in distributed database is a critical design issue and requires the most effort. It has the greater impact on the quality of the final solution and hence the operational efficiency of the system. Performance of the distributed database system is heavily dependent on allocation of data among the different sites over the network. The static allocation provides only the limited response to the change in workload. So, choosing an appropriate technique for allocation in the distributed database system is an important design issue. In this paper, a new dynamic data allocation for distributed database system has been proposed. The proposed methods reallocates data with respect to the changing data access patterns with time constraint. This methods will decrease the movement of data over the network and also improve the overall performance of the system. A new dynamic data allocation algorithm for non-replicated distributed database systems (DDS), namely the NNA algorithm. This algorithm reallocates data with respect to changing data access pattern for each fragment. In this algorithm, data is moved to a node which is the neighborhood and also placed in the path to the node with maximum access counter. This algorithm is very suitable for DDS in the networks which have low bandwidth and frequent requests for a data fragment come from different sites by providing data clustering. The simulation results show that for complex and large networks where the request for fragments generates more frequently or the fragment size is large, the NNA algorithm provides better response time and spends less time for moving fragments in the network.

Keywords: Distributed Databases, Static Data Allocation, Dynamic Data Allocation.

1 INTRODUCTION

Developments in database and networking technologies in the past few decades led to advances in distributed database systems. A DDS is a collection of sites connected by a communication network, in which each site is a database system in its own right, but the sites have agreed to work together, so that a user at any site can access data anywhere in the network exactly as if the data were all stored at the user's own site. The primary concern of a DDS is to design the fragmentation and allocation of the underlying database. Fragmentation unit can be a file where allocation issue becomes the file allocation problem. File allocation problem is studied extensively in the literature, started by Chu and continued for non-replicated and replicated models. Some studies considered dynamic file allocation. Various approaches have already been described the data allocation technique in distributed systems. Some methods are limit in their theoretical and implementation parts. Other strategies are ignoring the optimization of the transaction response time. The other approaches present exponential time of complexity and test their performance on specific types of network connectivity. Data allocation problem was introduced when Eswaran first proposed the data fragmentation. Studies on vertical fragmentation, horizontal fragmentation and mixed fragmentation were conducted. The allocation of the fragments is also studied extensively. In these studies, data allocation has been proposed prior to the design of a database depending on some static data access patterns and/or static query patterns. In a static environment where the access probabilities of nodes to the fragments never change, a static allocation of fragments provides the best solution. However, in a dynamic environment where these probabilities change over time, the static allocation solution would degrade the database performance. Initial studies on dynamic data allocation give a framework for data redistribution and demonstrate how to perform the redistribution process in minimum possible time. In a dynamic data allocation algorithm for non-replicated database systems is proposed named optimal algorithm, but no modeling is done to analyze the algorithm. …

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