In recent years, computer science research has focused on Grid applications, an important new field, distinguished from conventional distributed computing by its focus on large-scale computer, storage and other resource sharing, innovative applications, and, in many cases, high-performance orientation. It is generally believed that with the Grid concept a new major development is right now on the horizon. Scientists in a number of disciplines and developers of business applications are coming across limits in their ability to process, communicate, store and access exponentially increasing amounts of data. In tackling these problems, the Grid has the potential to have as profound an effect on the world, if not more, as the Web. The Grid concept derives its name from the analogy to a power grid because it delivers computing and data resources over the Internet, in much the same way that electricity is delivered over the power grid. The Grid research field can further be divided into two large sub-domains: computational grid and data grid. Whereas a computational grid is a natural extension of the former cluster computer, a data grid deals with the efficient management, placement and replication of large amounts of data. However, once data are in place, computational tasks can be run on the Grid using the provided data. The fundamental challenge is to make grid systems widely available and easy to use for a wide range of applications. This is crucial for accelerating their transition into fully operational environments. A significant amount of research for achieving these objectives is currently being started both in academia as well as industry.

Medical measurements such as the electricity information translation of blood sugar values can, if analyzed by the Human Body Channel Electricity Information Translation (HBCIT) process, help medical doctors specify appropriate illness diagnosis and monitor patient health. Efficient storage, management and analysis of the measured data volumes is an important research issue. To achieve better decisions, data from different, geographically distributed, cooperating hospitals may be linked (integrated) together and then analyzed. The data items can be associated with other complex patient information. Therefore, the analysis and processing of this data can be both data and compute intensive. Moreover, for medical applications a high level security has to be guaranteed. The Grid is a hot candidate for supporting such novel applications. The aim of this project is to develop a novel information infrastructure called the Medical Measurement Grid. It will support on-line diagnosis based on medical measurements.


Copyright CADGrid project, 2007
web analytics