An Introspection of Cloud Computing vs Grid Computing

Grid computing is emerging as a promising solution to some of the most vexing challenges facing e-Health. It also offers a powerful tool for other areas of healthcare such as drug discovery, as well as economic and weather forecasting, earthquake analysis, etc. In all these domains, grid computing easily outclasses traditional IT systems, in terms of its ability to cope cost effectively with their massive demands on computer-processing power, and the intensity of real-time data throughputs.

Whether one speaks of business travellers and tourists outside their home countries, the growing number of elderly with chronic diseases who cannot easily visit hospitals, or urgent, complex cases requiring consultations with a range of specialists, e-health means real-time, secure acquisition and access to extremely vast volumes of data from anywhere, at anytime.

From a pacemaker to an electronic health record, grid computing is seen as one of the ways to address these, as well as a wide array of associated challenges.

Both the robustness and the in-built fault tolerance of grids juxtaposes directly with the demand for 'always live' healthcare applications.

Other than access to distributed databases, the rapid data mining capabilities of grids are seen as enabling tools for a variety of epidemiological and biomedical applications. Grid computing is also proving itself in bioinformatics research, and has several proponents who swear about its advantages in terms of new drug design/discovery as well as personal medicine (or i-health).

At the moment, there are several e-health grid computing initiatives underway in Europe, at different stages - from research through pilot projects to implementation.