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Real-Time Virtual Resource: A Timely Abstraction for Embedded Systems

  • Aloysius K. Mok
  • Alex Xiang Feng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2491)

Abstract

Embedded systems comprise of tasks that have a wide variety of timing requirements, from the lax to the very stringent. The mixing of such tasks has been handled by specialized real-time schedulers, from the traditional cyclic executive dispatcher to sophisticated dynamic-priority schedulers. A common assumption of these real-time schedulers is the availability of global knowledge of the entire task set, and this assumption is required to ensure the schedulability of the time-critical tasks notwithstanding the interference of the less time-critical tasks. In this paper, we discuss the notion of a real-time virtual resource which abstracts the sharing of a physical resource such as a CPU by multiple time-critical tasks. Each real-time virtual resource is a virtual resource in the traditional sense of operating systems but its rate of service provision varies with time and is bounded. The real-time virtual resource abstraction allows tasks with wide-ranging timing criticality to be programmed as if they run on dedicated but slower CPUs such that global knowledge of the tasks is not necessary for schedulability analysis. More importantly, events or signals that are timing sensitive may retain their timeliness properties to within a bound under the real-time virtual resource abstraction, thereby permitting the composition of real-time tasks to preserve global timeliness properties.

Keywords

Task Group Virtual Resource Schedulability Analysis Regular Partition Virtual Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Aloysius K. Mok
    • 1
  • Alex Xiang Feng
    • 1
  1. 1.Department of Computer SciencesUniversity of Texas at AustinAustin

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