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Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers. [1] [2] The components of a distributed system communicate and coordinate their actions by passing messages to
The goal of a distributed network is to share resources, typically to accomplish a single or similar goal. [1] [2] Usually, this takes place over a computer network, [1] however, internet-based computing is rising in popularity. [3] Typically, a distributed networking system is composed of processes, threads, agents, and distributed objects. [3]
Distributed web crawling is a distributed computing technique whereby Internet search engines employ many computers to index the Internet via web crawling. Such systems may allow for users to voluntarily offer their own computing and bandwidth resources towards crawling web pages.
Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...
Stream processing is essentially a compromise, driven by a data-centric model that works very well for traditional DSP or GPU-type applications (such as image, video and digital signal processing) but less so for general purpose processing with more randomized data access (such as databases). By sacrificing some flexibility in the model, the ...
CADP [1] (Construction and Analysis of Distributed Processes) is a toolbox for the design of communication protocols and distributed systems. CADP is developed by the CONVECS team (formerly by the VASY team) at INRIA Rhone-Alpes and connected to various complementary tools.
Distributed data processing. Distributed data processing [1] (DDP) [2] was the term that IBM used for the IBM 3790 (1975) and its successor, the IBM 8100 (1979). Datamation described the 3790 in March 1979 as "less than successful." [3] [4] Distributed data processing was used by IBM to refer to two environments: IMS DB/DC; CICS/DL/I [5] [6]
DaaS began primarily in Web mashups and, since 2015, has been increasingly employed both commercially, and within organizations such as the United Nations. [5]Traditionally, most organisations have used data stored in a self-contained repository, for which software was specifically developed to access and present the data in a human-readable form.