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What are the significant differences between Cloud Computing and Grid Computing ? What are the precise definations and target application domains for both ? I'm looking for conceptual insights along with technicalities.
Like Windows Azure is a Cloud OS, do we have anytihng such for Grid Computing ?
In past I did work on distributed and parallel computing and I used the librariries like PVM and MPI for processing distribution. Out of curiosity I wanted to know If Grid Computing is distributed computing extended over internet ?
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In grid computing, resources are used in collaborative pattern, and also in grid computing, the users do not pay for use. 1. Cloud computing is a Client-server computing architecture. While it is a Distributed computing architecture.
In grid computing you donate *your* hardware and software resources so that either your own or others' computations/data are performed/stored on them. And in clouds you send your data/rpgorams "somewhere" (you don't even know where) and buy some "something" (a very volatile something) to process them.
Grid computing is more economical. It splits the work and distributes it over the network on computers increasing the efficiency as well. Cloud computing is costlier and requires initial setup. But it is faster and has quicker data restoration.
ABSTRACT Grid and Cloud both have similarities like both are used to share recourses e.g. computational power, storage, application, equipments and many more. That don't mean both are equals. In this paper we have discussed about Grid Computing and Cloud Computing.
Grid computing is where more than one computer coordinates to solve a problem together. Often used for problems involving a lot of number crunching, which can be easily parallelisable.
Cloud computing is where an application doesn't access resources it requires directly, rather it accesses them through something like a service. So instead of talking to a specific hard drive for storage, and a specific CPU for computation, etc. it talks to some service that provides these resources. The service then maps any requests for resources to its physical resources, in order to provide for the application. Usually the service has access to a large amount of physical resources, and can dynamically allocate them as they are needed.
In this way, if an application requires only a small amount of some resource, say computation, then the service only allocates a small amount, say on a single physical CPU (that may be shared with some other application using the service). If the application requires a large amount of some resource, then the service allocates that large amount, say a grid of CPUs. The application is relatively oblivious to this, and all the complex handling and coordination is performed by the service, not the application. In this way the application can scale well.
For example a web site written "on the cloud" may share a server with many other web sites while it has a low amount of traffic, but may be moved to its own dedicated server, or grid of servers, if it ever has massive amounts of traffic. This is all handled by the cloud service, so the application shouldn't have to be modified drastically to cope.
A cloud would usually use a grid. A grid is not necessarily a cloud or part of a cloud.
Wikipedia articles: Grid computing, Cloud computing.
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