Please use this identifier to cite or link to this item: http://theses.ncl.ac.uk/jspui/handle/10443/264
Title: Exploiting dynamic deployment in a distributed query processor for the grid
Authors: Mukherjee, Arijit
Issue Date: 2008
Publisher: Newcastle University
Abstract: The adoption of the "Web Services" model for building a Grid framework created a considerable shift from the original concept of Grid which was based on "distributed job scheduling". The requirement for the access and integration of heterogeneous data resources over the Grid, and the advances in service-oriented data access standards led to the development of a service-oriented distributed query processor, which forms the basis of this thesis. The adoption of service-orientation raised the need for a framework which would allow demanddriven deployment of Web Services on available resources. Research into such concepts led to the development of DynaSOAr, a framework which proposed an alternative approach to distributed job scheduling by focussing entirely on the concept of services, rather than the more traditional jobs. DynaSOAr allows services to be deployed on demand to meet changing performance requirements and exploits the advances made in virtualization technologies to support the deployment of services and databases. The thesis describes a system designed to exploit dynamic deployment features within the context of distributed query processing on the Grid, and argues that such features benefit query evaluation by creating a loose coupling between the services and the available resources. The extended distributed query processing system is able to collocate various entities, such as the evaluation and analysis services with the data, to reduce data traffic over the network, and is also able to reconfigure itself to improve performance by dynamically deploying database snapshots. The thesis evaluates the dynamic distributed query processing framework through several experiments which explore its behaviour in a variety of scenarios.
Description: PhD Thesis
URI: http://hdl.handle.net/10443/264
Appears in Collections:School of Computing Science

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