Real-time computing

Real-time computing (RTC) is the computer science term for hardware and software systems subject to a "real-time constraint", for example from event to system response.[1] Real-time programs must guarantee response within specified time constraints, often referred to as "deadlines".[2]

The term "real-time" is also used in simulation to mean that the simulation's clock runs at the same speed as a real clock.

Real-time responses are often understood to be in the order of milliseconds, and sometimes microseconds. A system not specified as operating in real time cannot usually guarantee a response within any timeframe, although typical or expected response times may be given. Real-time processing fails if not completed within a specified deadline relative to an event; deadlines must always be met, regardless of system load.

A real-time system has been described as one which "controls an environment by receiving data, processing them, and returning the results sufficiently quickly to affect the environment at that time".[3] The term "real-time" is used in process control and enterprise systems to mean "without significant delay".

Real-time software may use one or more of the following: synchronous programming languages, real-time operating systems (RTOSes), and real-time networks, each of which provide essential frameworks on which to build a real-time software application.

Systems used for many safety-critical applications must be real-time, such as for control of fly-by-wire aircraft, or anti-lock brakes, both of which demand immediate and accurate mechanical response.[4]

  1. ^ "FreeRTOS – Open Source RTOS Kernel for small embedded systems – What is FreeRTOS FAQ?". FreeRTOS. Retrieved 2021-03-08.
  2. ^ Ben-Ari, Mordechai; "Principles of Concurrent and Distributed Programming", ch. 16, Prentice Hall, 1990, ISBN 0-13-711821-X, p. 164
  3. ^ Martin, James (1965). Programming Real-time Computer Systems. Englewood Cliffs, New Jersey: Prentice-Hall Incorporated. p. 4. ISBN 978-0-13-730507-0.
  4. ^ Kant, Krishna (May 2010). Computer-Based Industrial Control. PHI Learning. p. 356. ISBN 9788120339880. Retrieved 2015-01-17.

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