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Grid computing is a term referring to the combination of computer resources from multiple administrative domains to reach a common goal. The grid can be thought of as a distributed system with non-interactive workloads that involve a large number of files. What distinguishes grid computing from conventional high performance computing systems such as cluster computing is that grids tend to be more loosely coupled, heterogeneous, and geographically dispersed. Although a grid can be dedicated to a specialized application, it is more common that a single grid will be used for a variety of different purposes. Grids are often constructed with the aid of general-purpose grid software libraries known as middleware.
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The grid computing concept isn't a new one. It's a special kind of distributed computing. In distributed computing, different computers within the same network share one or more resources. In the ideal grid computing system, every resource is shared, turning a computer network into a powerful supercomputer.
Grid Architecture
A grid's architecture is often described in terms of "layers", where each layer has a specific function. The higher layers are generally user-centric, whereas lower layers are more hardware-centric, focused on computers and networks.
The lowest layer is the network, which connects grid resources.
Above the network layer lies the resource layer: actual grid resources, such as computers, storage systems, electronic data catalogues, sensors and telescopes that are connected to the network.
The middleware layer provides the tools that enable the various elements (servers, storage, networks, etc.) to participate in a grid. The middleware layer is sometimes the "brains" behind a computing grid!
The highest layer of the structure is the application layer, which includes applications in science, engineering, business, finance and more, as well as portals and development toolkits to support the applications. This is the layer that grid users "see" and interact with. The application layer often includes the so-called service ware, which performs general management functions like tracking who is providing grid resources and who is using them.
History of Grid
Grid computing didn't just come out of nowhere. It grew from previous efforts and ideas, such as those listed below:
Grid computing immediate ancestor is "metacomputing", which dates back to around1990. Met computing was used to describe efforts to connect US supercomputing centers. Larry Smarr, a former director of the National Center for Supercomputing Applications in the US, is generally credited with popularizing the term.
FAFNER and I-WAY were cutting-edge metacomputing projects in the US, both conceived in 1995. Each influenced the evolution of key grid technologies.
FAFNER (Factoring via Network-Enabled Recursion) aimed to factorize very large numbers, a challenge very relevant to digital security. Since this challenge could be broken into small parts, even fairly modest computers could contribute useful power. Many FAFNER techniques for dividing and distributing computational problems were forerunners of technology used for SETI@home and other "cycle scavenging" software.
I-WAY (Information Wide Area Year) aimed to link supercomputers using existing networks. One of I-WAY's innovations was a computational resource broker, conceptually similar to those being developed for grid computing today. I-WAY strongly influenced the development of the Globus Project, which is at the core of many grid activities, as well as the LEGION project, an alternative approach to distributed supercomputing.
Grid computing was born at a workshop called "Building a Computational Grid", held at Argonne National Laboratory in September 1997.
Types of Grid
Computational Grid: These grids provide secure access to huge pool of shared processing power suitable for high throughput applications and computation intensive computing.
Data Grid: Data grids provide an infrastructure to support data storage, data discovery, data handling, data publication, and data manipulation of large volumes of data actually stored in various heterogeneous databases and file systems.
Collaboration Grid: With the advent of Internet, there has been an increased demand for better collaboration. Such advanced collaboration is possible using the grid. For instance, persons from different companies in a virtual enterprise can work on different components of a CAD project without even disclosing their proprietary technologies.
Network Grid: A Network Grid provides fault-tolerant and high-performance communication services. Each grid node works as a data router between two communication points, providing data-caching and other facilities to speed up the communications between such points.
Utility Grid: This is the ultimate form of the Grid, in which not only data and computation cycles are shared but software or just about any resource is shared. The main services provided through utility grids are software and special equipments. For instance, the applications can be run on one machine and all the users can send their data to be processed to that machine and receive the result back.

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