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Rate-monotonic analysis for real-time industrial computing

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3 Author(s)
Klein, M.H. ; Carnegie Mellon Univ., Pittsburgh, PA, USA ; Lehoczky, J.P. ; Rajkumar, R.

Issues of real-time resource management are pervasive throughout industrial computing. The underlying physical processes of many industrial computing applications impose explicit timing requirements on the tasks processed by the computer system. These timing requirements are an integral part of the correctness and safety of a real-time system. It is tempting to think that speed (for example, processor speeds or higher communication bandwidths) is the sole ingredient in meeting system timing requirements, but speed alone is not enough. Proper resource-management techniques also must be used to prevent, for example, situations in which long, low priority tasks block higher priority tasks with short deadlines. One guiding principle in real-time system resource management is predictability, the ability to determine for a given set of tasks whether the system will be able to meet all of the timing requirements of those tasks. Predictability calls for the development of scheduling models and analytic techniques to determine whether or not a real-time system can meet its timing requirements. The author illustrates an analysis methodology, rate monotonic analysis, for managing real-time requirements in a distributed industrial computing situation. The illustration is based on a comprehensive robotics example drawn from a typical industrial application.<>

Published in:

Computer  (Volume:27 ,  Issue: 1 )