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Grid Computing vs. Cloud Computing
How Do They Differ?
Let’s begin by defining our terms here. Cloud computing is defined in detail here. For the purposes of
this article, we can see it as a loose term covering a range of technologies which result in the
delivery of computing as a metered service rather than a strict product. So, software, information
and shared resources are delivered over a network, (typically the Internet) to computers and devices
such as smartphones, dumb terminals etc. as a utility, in much the same way electricity is delivered.
Grid computing is a slightly more complex idea reflecting its specialised nature and is a subset of
cloud computing. Grid computing consists of applying the resources of many computers, typically
PCs or UNIX workstations plus multiple storage devices and redundant interconnections, which
together form what seems to the users as a single highly available system. These are usually applied
to a scientific/technical problem requiring vast numbers of computer processing cycles and/or
access to large amounts of data in a network to a single problem at the same time. Grids are a form
of distributed computing creating a “super virtual computer” composed of many networked loosely
coupled computers acting together to perform large tasks.
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At the risk of repetition, clustering computers; a technology in use since the 1980s consists of taking
many computers and using a piece of clustering middleware making them act in concert so as to
appear a single system. The difference between clustering and grid computing is that grids are more
heterogeneous, loosely coupled, and geographically dispersed. Although a single grid can work on
one application alone, a grid is usually used for a variety of purposes. Again this cluster appears to
the user as a single machine that delivers very high levels of availability owing to the redundancy
inherent in the use of many distributed machines.
One of the main advantages of grid computing is that it is a low cost method of facilitating parallel
processing. This is where a program is divided into various instructions which are in turn sent to
various processors simultaneously with the object of reducing time to complete the whole. These
characteristics have advantages in resolving certain problems; in data mining for instance, there is a
requirement for multiple searches of a static database. In artificial intelligence, there is the need to
analyse multiple alternatives, such as in a chess game.
Grid computing appears promising for three reasons:
1. The ability to make cost-effective use of a defined amount of computer resources.
2. As a means of solving problems that can only be approached with an enormous amount of
computing power.
3. Grid computing suggests the resources of many computers may be cooperatively and even
synergistically harnessed and managed collaboratively toward a common objective.
In some grid computing systems, computers may act collaboratively rather than being directed by
one single computer acting as a manager. A likely field for grid computing is in pervasive computing
applications; i.e. where computers pervade our environment without our immediate awareness.
A well-known example of grid computing in the public sphere is http://setiathome.berkeley.edu/
which is the SETI (Search for Extraterrestrial Intelligence) @Home project where thousands of
people are sharing the unused processor cycles of their PCs in the vast search for signs of intelligent
signals from outer space by analysing data from radio telescopes.
Bull Terrier Systems Ltd. PO Box 861, Oxford OX1 9NJ.
Web: http://www.managedserviceexpert.com/ email: [email protected]
Company Registration Number: 5417836. VAT Registration Number 860 5042 47