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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]
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
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 ...
Distributed Data Management Architecture (DDM) is IBM's open, published software architecture for creating, managing and accessing data on a remote computer. DDM was initially designed to support record-oriented files; it was extended to support hierarchical directories, stream-oriented files, queues, and system command processing; it was further extended to be the base of IBM's Distributed ...
Formally, we represent each event in a distributed flow as a quadruple of the form (x,t,k,v), where x is the location (e.g., the network address of a physical node) at which the event occurs, t is the time at which this happens, k is a version, or a sequence number identifying the particular event, and v is a value that represents the event payload (e.g., all the arguments passed in a method ...
Some researchers have made a functional and experimental analysis of several distributed file systems including HDFS, Ceph, Gluster, Lustre and old (1.6.x) version of MooseFS, although this document is from 2013 and a lot of information are outdated (e.g. MooseFS had no HA for Metadata Server at that time).
The objectives of Distributed Artificial Intelligence are to solve the reasoning, planning, learning and perception problems of artificial intelligence, especially if they require large data, by distributing the problem to autonomous processing nodes (agents). To reach the objective, DAI requires:
Distributed Processing Technology Corporation (DPT) was an American computer hardware company active from 1977 to 1999. Founded in Maitland, Florida , DPT was an early pioneer in computer storage technology, popularizing the use of disk caching in the 1980s and 1990s.