Grid Computing – refers to the concept of flexible use of computing resources on the network, you can configure a virtual high performance computer, so that you can make the flexible allocation of resources.
Grid computing usually consists of one main computer that distributes information and tasks to a group of networked computers to accomplish a common goal. Grid computing is often used to complete complicated or tedious mathematical or scientific calculations.
In a large enterprise, hundreds or thousands of desktop machines sit idle at any given moment. Even when a user is at the computer reading the screen and not typing or clicking, it constitutes idle time. These unused cycles can be put to use on large computational problems. In the same way, the millions of users on the Internet waste massive amounts of machine cycles every minutes. Gathered up the computer resources of such a surplus, and effectively utilization of demand is the basic idea of grid computing.
Advantages of Grid Computing
- Easier to collaborate with other organizations.
- Make better use of existing hardware.
- No need to but huge servers for applications that can be split up and farmed out to smaller commodity type servers.
- Grid environments are much more modular and don’t have single points of failure. If one of the servers/desktops within the grid fail there are plenty of other resources able to pick the load.
- Jobs can be executed in parallel speeding performance
- Can solve larger, more complex problems in a shorter time.
Disadvantages of Grid Computing
- Grid software and standards are still evolving.
- Learning curve to get started.
- Non-interactive job submission.
- You may need to have a fast interconnect between compute resources.
- Licensing across many servers may make it prohibitive for some applications.
- Many groups are reluctant with sharing resources even if it benefits everyone involved.