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Edge computing is a distributed computing model that brings computation and data storage closer to the sources of data. More broadly, it refers to any design that pushes computation physically closer to a user, so as to reduce the latency compared to when an application runs on a centralized data centre .
Multi-access edge computing (MEC), formerly mobile edge computing, is an ETSI-defined [1] network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network [2] [3] and, more in general at the edge of any network. The basic idea behind MEC is that by running applications and ...
The OpenFog Consortium was an association of major tech companies aimed at standardizing and promoting fog computing.. Fog computing [1] [2] or fog networking, also known as fogging, [3] [4] is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone.
Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP–Intel alliance [1] to describe a computing paradigm that researchers had been investigating since the early 1980s. [2] This paradigm is also called Independence architectures.
In computer networking, an edge device is a device that provides an entry point into enterprise or service provider core networks. [1] Examples include routers , [ 2 ] routing switches , integrated access devices (IADs), multiplexers, and a variety of metropolitan area network (MAN) and wide area network (WAN) access devices.
Data can be kept statically in nodes if most computations happen locally, and only changes on edges have to be reported to other nodes. An example of this is simulation where data is modeled using a grid, and each node simulates a small part of the larger grid. On every iteration, nodes inform all neighboring nodes of the new edge data.
In computing, multiple instruction, multiple data (MIMD) is a technique employed to achieve parallelism. Machines using MIMD have a number of processor cores that function asynchronously and independently. At any time, different processors may be executing different instructions on different pieces of data.
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