ABSTRACT
Definition of Grid Computing :
A parallel processing architecture in which CPU resources are shared across a network, and all machines function as one large supercomputer. It allows unused CPU capacity in all participating machines to be allocated to one application that is extremely computation intensive and programmed for parallel processing.
History
The term Grid computing originated in the early 1990s as a metaphor for making computer power as easy to access as an electric power grid in Ian Foster and Carl Kesselmans seminal work, "The Grid: Blueprint for a new computing infrastructure". CPU scavenging and volunteer computing were popularized beginning in 1997 by distributed.net and later in 1999 by SETI@home to harness the power of networked PCs worldwide, in order to solve CPU-intensive research problems.
The ideas of the grid (including those from distributed computing, object oriented programming, cluster computing, web services and others) were brought together by Ian Foster, Carl Kesselman and Steve Tuecke, widely regarded as the "fathers of the grid." They led the effort to create the Globus Toolkit incorporating not just computation management but also storage management, security provisioning, data movement, monitoring and a toolkit for developing additional services based on the same infrastructure including agreement negotiation, notification mechanisms, trigger services and information aggregation. While the Globus Toolkit remains the defacto standard for building grid solutions, a number of other tools have been built that answer some subset of services needed to create an enterprise or global grid.
In practice, participating computers also donate some supporting amount of disk storage space, RAM, and network bandwidth, in addition to raw CPU power. Since nodes are apt to go "offline" from time to time, as their owners use their resources for their primary purpose, this model must be designed to handle such contingencies.
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