Uncertainty Theories for Real-Time Systems

Bandyszak, Torsten; Weyer, Thorsten; Daun, Marian

doi:10.1007/978-981-287-251-7_64

Uncertainty Theories for Real-Time Systems

Torsten Bandyszak³,
Thorsten Weyer³ &
Marian Daun³

Reference work entry
First Online: 09 August 2022

1513 Accesses
2 Citations

Abstract

Real-time systems are typically reactive embedded software-intensive systems that are part of a larger technical system such as a vehicle or an airplane. Real-time systems perform time-critical tasks, which depend on timely processing of context data obtained from sensors, and making decisions as well as performing actions based on the assessed context situation. Real-time systems thus face various uncertainties that may occur during operation. To cope with uncertainties in real-time execution, this chapter introduces general taxonomies and theories for handling uncertainty and relates these to the field of real-time computing. To that end, a reference model is proposed, which specifically determines sources of uncertainty in the context of a real-time system when it is in operation. Building upon the reference model, an overview of uncertainty handling approaches that specifically address real-time concerns and can be utilized to handle the different uncertainty in real-time systems is given. Finally, since real-time systems have to be constructed in such a way that they are able to handle uncertainties at runtime, this chapter also regards the need to identify, model, and analyze potential uncertainties that can occur during operation already in the engineering of real-time systems.

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Bandyszak, T., Weyer, T., Daun, M. (2022). Uncertainty Theories for Real-Time Systems. In: Tian, YC., Levy, D.C. (eds) Handbook of Real-Time Computing. Springer, Singapore. https://doi.org/10.1007/978-981-287-251-7_64

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DOI: https://doi.org/10.1007/978-981-287-251-7_64
Published: 09 August 2022
Publisher Name: Springer, Singapore
Print ISBN: 978-981-287-250-0
Online ISBN: 978-981-287-251-7
eBook Packages: EngineeringReference Module Computer Science and Engineering

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