A Software Tool and a Network Simulation for Improving Quality of Service Performance in Distributed Database Management Systems

A Software Tool and a Network Simulation for Improving Quality of Service Performance in Distributed Database Management Systems

Ismail Omar Hababeh (United Arab Emirates University, UAE) and Muthu Ramachandran (Leeds Metropolitan University, UK)
DOI: 10.4018/978-1-60566-731-7.ch018
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The efficiency and effectiveness of Quality of Service QoS performance methods in a Distributed Database Management System DDBMS environment are measured by their successfully simulation on the real world applications. To achieve the goals of the simulation modules and to analyze the behaviour of the distributed database network system and the QoS performance methods of fragmentation, clustering and allocation, an integrated software tool for a DDBMS supported by the OPNET is designed and presented. It is developed to wisely distribute the data among several sites on a database network system, effectively enhance the QoS performance at lower cost, successfully provide reliability to the DDBMS in case of site failure, and efficiently increase the data availability where multiple copies of the same data are allocated to different sites. The integrated software tool supply the database administrators with a software that is friendly use, easy to navigate, comprehensive, and expandable that simulate the techniques of database fragmentation, clustering network sites, and fragment allocation and replication in a DDBMS. The tool performs the database transactions operations efficiently and effectively through reliable forms that allow the database administrators to control over their operations and follow up the system improvements and QoS enhancements. The performance evaluation and simulation results indicate that the proposed methods significantly improves the QoS performance in the DDBMS even with manageable extra information, network sites, communication and processing cost functions.
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2. The Ddbms Applications In The Literature

The increasing success of relational database technology in data processing is due, in part, to the availability of nonprocedural languages, which can significantly improve application development and end-user productivity Ozsu and Valduriez (1999).

Apers (1988) addressed the necessity of supplying a Database Management System DBMS with tools to efficiently process queries and to determine allocations of the data such that the availability is increased, the access time is decreased, and/or the overall usage of resources is minimized.

Hoffer, Prescott, and McFadden (2004) have investigated a comparison between different types of database systems and described the results in terms of reliability, expandability, communications overhead, manageability, and data consistency. They conclude that there has been an increase in the demand for DDBMS tools that interconnect databases residing in a geographically distributed computer network.

Greene et. al (2008) noted that the National Virtual Observatory (NVO) Open SkyQuery portal allows users to query large, physically distributed databases of astronomical objects. Queries can be generated through a simple forms-based interface or through an advanced query page in which the user generates a SQL-type query. The portal provides both a simple form and advanced query interface for users to perform distributed queries to single or multiple SkyNodes. However, Open SkyQuery currently limits the number of matches to 5000, data duplication is still available between queries, and no disjoint database fragments are generated by this application.

Key Terms in this Chapter

Server Load: Determines the speed of the server in terms of (bits/sec)

DDBMS: Distributed Database management system is database software that manages and controls access to the database.

DFCA: Distributed Fragmentation Clustering and Allocation modelling technique

SCFG: Segment Creator and Fragment Generator is a distributed database method used for creating database segments and generating fragments.

QoS Performance Improvement: Quality of Service Performance Improvement

Network Delay: The maximum time required for the network system to reach the steady state and measured in millisecond

FLC: Fragment Life Cycle is a distributed database process which represents the architecture of the Segments Creator and Fragments Generator.

SQL: Structural Query Language

OPNET: Network simulation software

Network Simulation: Simulation the DDBMS network system performance

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