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Quality of context and grid computing: An user satisfaction and system performance trade off model

The trend of grid computing available on the Internet has generated challenges to the allocation of resources provided by this type of environment. Considering the user's satisfaction, many of these challenges can be solved by the quality of experience paradigm that takes into account several context parameters. Considering the resources utilization, the quality of context paradigm can be used to improve the system performance. Once that a grid platform is a context sensitive system, so its possible to deal jointly with user's satisfaction and system performance. In this sense, the quality of context can be used to process the context informations and provide several management decisions. So, in this paper we propose a model to obtain runtime improvement for individual users, and improve the global system performance using quality of context. Experimental results shows improvements up to 53% in the runtime jobs, and some improvement in the global environment performance when applied our model in a grid scenario.