Distributed computing is used for various applications, from data processing to control systems. It allows for simultaneous processing of large datasets and is used in information sharing networks, backups, scientific modeling, and industrial control systems.
Distributed computing can be used for many applications, from mundane storage to tasks that place a heavy workload on the central processing unit (CPU). Today’s telecommunications network and the Internet itself are examples of ubiquitous distributed computing models. Each computer is self-contained but contributes to the larger system, whether for communications and information, data processing, modeling or control systems.
Computer-based computing forces all data sets to be funneled through that computer’s processor one set at a time. When there are large amounts of data to process, this can be time consuming because each set of data needs to be resolved before the next one can be started. Distributed computing allows for multiple parts of a large dataset to be processed simultaneously.
Information sharing networks make heavy use of distributed computing. Today’s telecommunications network and the Internet are effectively one giant database. The information stored on all connected computers is managed autonomously but can be requested through the network by another resource.
Whether requesting a web page or a phone number, a member of a distributed network processes that request and sends the information to the requestor. This also applies to the concept of distributed backups. Server farms and data centers use distributed computing to provide redundancy in backups, so that all critical information is safe from the potential failure of a server within the network.
Distributed computing can also be used to rapidly process large amounts of information, breaking it into discrete chunks that can then be recombined into the larger whole. This allows for widespread analysis of the data set. Other times, this can result in direct input such as rendering farms where each frame of a computer-generated scene is split into parts which are then each handled by computers in the distributed cluster. The completed segments are then combined back into the whole.
Another use for distributed computing is for large-scale scientific modeling. Environmental models can have a large number of variables that a single computer would have to process one by one before incorporating them into a final model. Distributed computing makes it possible to split each of these variables into other systems and generate the results much faster, in most cases in real time.
Industrial control systems as well as aircraft control systems make use of distributed computing in very direct ways. These clusters of computers monitor both types of systems in real time, constantly reporting the results to each other and to human operators. In the event of a malfunction or failure in the industrial process, the network can immediately identify where the malfunction is and work around it until it is fixed. Similarly, aircraft control systems can quickly identify traffic patterns, trajectories and clear runways to allow aircraft to operate safely and efficiently at airports, as well as navigate around problem areas caused by weather disruptions.
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