期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2007
卷号：7
期号：12
页码：114-123
出版社：International Journal of Computer Science and Network Security
摘要：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. However, the current grid computing implantations introduce new challenges for remote real time visualization such as resources discovery and real time automatic resources selection. This paper investigates how the automatic resources selection mechanism could be used to support real time remote visualization of large medical datasets on the grid environment. We show our Adaptive resources selection framework for grid enabled visualization pipeline. Our results shows better performance of distributed parallel Isosurface of large partitioned datasets implemented as grid services. We support our findings with practical implementation of grid enabled visualization prototype, and our proposed grid mapping function algorithm for automatic resources selection to visualize large medical datasets, (circa 11 million polygons) on modest resources machine.
