Grid computing is highly dynamic in nature where resources are subject to change due to performance degradation and node failure. The resources include processing elements, storage, network, and so on; they come from the interconnection of parallel machines, clusters, or any workstation. One of the main properties of these resources is to have changing characteristics even during the execution of an application. Thus, resource usage by applications cannot be static during run-time; neither can change in resources be considered as faults. Therefore, Grrid application designers must keep in mind that resources and resource management are highly dynamic within Grid architectures.\ud \ud Grdi resource brokering is introduced to simplify resource discovery, selection, and job submission for Grid application. However, it is the responsibility of a Grid resource broker to distribute jobs among heterogeneous resources and optimise the resource usage. As a result, a Grid resource broker should have the capablility to adapt to these changes and take appropriate actions to improve performance of various computing applications. To adapt to the Grid resource changes, an adaptive service is introduced in this research. The adaptive service consists of a monitoring tool, decision manager, and migration engine to ensure the job finishes at the time specified. The adaptive service supports job migration during run-time to ensure timely job completion.\ud \ud Our work in this research shows a Grid test-bed and White Rose Grid implementation of an adaptive service that supports job migration during run-time to ensure timely job completion. Performance prediction is used to estimate expected job completion time and determine whether any onserved performance degradation is likely to result in failure to meet a user specified deadline. A key feature of our approach is that the user is not required to install additional software or make complex alterations to their code requiring specialist Grid computing knowledge. This is achieved using a reflective technique to bind the adaptive service components to the user's code. Also, this research proves the adaptive service overhead is very minimal. The adaptive service is a viable contender for future Grid resource brokering implementation
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