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Grid computing uses computer resources across domains to achieve common goals. Nodes are loosely coupled to a central computer, creating a powerful virtual machine. It can be used for P2P file sharing and two-way communication. Disadvantages include unreliable connections and incomplete downloads.
Grid computing does its job by using computer resources in different administrative domains to achieve common goals. Some grid computing applications have their own user interface. In such cases, the connection is controlled by the computer operator, such as peer to peer (P2P) file sharing networks. Others are less obvious background tasks, such as processing scientific data during a computer’s idle time.
Grid computing is often called distributed computing because project files are distributed among several nodes. The node consists of a single Internet-connected machine loosely coupled to a central computer that can be hundreds of miles away. This central machine is connected to hundreds, even thousands, of other nodes, all of which receive packets, process data, and send requests. Depending on the structure of the grid, individual nodes may or may not be able to communicate with each other.
One of the major benefits gained from grid computing applications is the loose coupling of nodes to the central computer to create a very powerful virtual machine. This machine is, essentially, a supercomputer capable of processing data at a much faster rate than any single computer on the grid. Such super computer grid technology has been effectively used to study and process data relating to earthquakes, weather conditions and even the possibility of life on other planets.
Another advantage of using this type of processing is the two-way communication between the node and the central computer. The grid computing process was originally designed with the idea that the Internet should be more like an electrical grid. The power grid system sends and receives information from individual points to track usage statistics. This same communication channel principle makes it possible to design grid computing process applications for Internet services at economical prices based on usage quantities.
Among other applications of grid computing, this programming structure can also be useful in forming P2P file sharing networks. In networks of this type, people from all corners of the globe can share data, including audio, video and text files. The grid computing system allows the user of the node to find the desired files using a coordinated search function from the central system and other processing points anywhere on the network.
The disadvantage of this type of service lies in the connections of the nodes. Since this network involves a diverse group of Internet users, the various nodes can be connected by different means. As a result, some users may have a very slow upload connection or an unreliable connection to the network. If a user disconnects the computer with the hosted files before the download is complete, the file might not be available until the computer is brought back online.
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