Grid computing offers a model for solving massive computational problems using large numbers of computers arranged as clusters embedded in a distributed telecommunications infrastructure.
Grid computing has the design goal of solving problems too big for any single supercomputer, whilst retaining the flexibility to work on multiple smaller problems. Thus grid computing provides a multi-user environment.
This implies the use of secure authorization techniques to allow remote users to control computing resources.
Grid computing involves sharing heterogenous resources (based on different platformss, hardware/software [[computer architecture | architectures]], computer languages), located in different places belonging to different administrative domains over a network using open standards. In short, it involves virtualizing computing resources. Functionally, one can classify grids as:
- Computational Grids (including CPU scavenging grids), or
- Data Grids.
Globus has protocols to handle
- Resource management: Grid Resource Management Protocol (GRAM)
- Information Services: Monitoring and Discovery Service (MDS)
- Data Movement and management: Global Access to Secondary Storage (GASS) and GridFTP
XML-based web services offer a way for accessing diverse services/applications in a distributed environment. As of 2003 the world of Grid computing and Web Services have started to converge to offer Grid as a web service (Grid Service). The Open Grid Services Architecture (OGSA) has defined this environment, which will offer several functionalities adhering to the semantics of the Grid Service.
Grid offers a way to solve Grand Challenge problems like protein folding, drug discovery, financial modelling, earthquake simulation, climate/weather modelling etc. Grids offer a way of using the information technology resources optimally in an organisation. They also offer a means to offer information technology as a utility bureau for commercial clients, with those clients paying only for what they use, as with electricity or water.
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