enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Distributed data processing - Wikipedia

    en.wikipedia.org/wiki/Distributed_data_processing

    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]

  3. Distributed Data Management Architecture - Wikipedia

    en.wikipedia.org/wiki/Distributed_Data...

    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 ...

  4. RM-ODP - Wikipedia

    en.wikipedia.org/wiki/RM-ODP

    The RM-ODP view model, which provides five generic and complementary viewpoints on the system and its environment.. Reference Model of Open Distributed Processing (RM-ODP) is a reference model in computer science, which provides a co-ordinating framework for the standardization of open distributed processing (ODP).

  5. Distributed algorithm - Wikipedia

    en.wikipedia.org/wiki/Distributed_algorithm

    A distributed algorithm is an algorithm designed to run on computer hardware constructed from interconnected processors. Distributed algorithms are used in different application areas of distributed computing , such as telecommunications , scientific computing , distributed information processing , and real-time process control .

  6. Distributed data flow - Wikipedia

    en.wikipedia.org/wiki/Distributed_data_flow

    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 ...

  7. Stream processing - Wikipedia

    en.wikipedia.org/wiki/Stream_processing

    Stream processing is especially suitable for applications that exhibit three application characteristics: [citation needed] Compute intensity, the number of arithmetic operations per I/O or global memory reference. In many signal processing applications today it is well over 50:1 and increasing with algorithmic complexity.

  8. Distributed ledger - Wikipedia

    en.wikipedia.org/wiki/Distributed_ledger

    The primary advantage of this distributed processing pattern is the lack of a central authority, which would constitute a single point of failure. When a ledger update transaction is broadcast to the P2P network, each distributed node processes a new update transaction independently, and then collectively all working nodes use a consensus ...

  9. Distributed computing - Wikipedia

    en.wikipedia.org/wiki/Distributed_computing

    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