Adaptive Resources Selection Framework for Grid Enabled Visualization Pipeline

Scientific data visualization is a process of transforming numerical data into a pictorial format conceivable by humans. The datasets generated by medical detectors and simulations is increasing in size and complexity. Additionally, the conventional desktop computers are not sufficient to process this datasets due to memory overwhelming phenomenon which causes the desktop to be in unresponsive state. The current implementation of remote visualization techniques specifically real time visualization takes the direction of reducing the size of the datasets which is known to give less details and precision of the visualization. On the top of that, the increasing size of datasets and the continuous demand for computational power results an urgent need for grid computing infrastructure for real time remote visualization.