• "The first revolution is when you change your mind
    about how you look at things
    and see that there might be another way to look at it
    that you have not been shown."

    --Gil Scott-Heron, "The Revolution Will Not Be Televised"
  • Updated on 26 December 2019 at 4:55 pm

    Real-Time for the Real World

    E. Douglas Jensen

    Work-in-progress preview of a work-in-progress book:

    Introduction to Fundamentals of Timeliness
    and Predictability in Dynamically Real-Time Systems
    [Jensen 2020]


    Informally, a system is a “real-time” one if its core properties of timeliness and predictability of timeliness are integral to its logic, not just performance measures. In general, those properties are dynamic due to intrinsic aleatory and epistemic uncertainties in its system model and its application environment. That constitutes “dynamically real-time.” Despite such uncertainties, dynamically real-time systems have application-specific kinds and degrees of mixed criticality—including even the most extreme safety-critical cases (for military combat, cf. “the fog of war”). Traditional real-time computing systems are a narrow special case whose system models and core properties are predominantly static and periodic. They have very limited (albeit often important) applicability—hence the gradual increase of research on “firm” and stochastic real-time computing. Many dynamically real-time systems already exist, created in application domains outside of, and unseen by, the real-time computing field. These experiences are usually held as enterprise proprietary or government classified. However, dynamically real-time systems suffer from the lack of a coherent foundation for expressing and achieving application-specific timeliness and predictability.  This book introduces one approach to that. Timeliness is dynamically expressive using my time/utility (née time/value) functions and utility accrual (née value-based) scheduling paradigm [Jensen 77] [Jensen+ 85]. Predictability of dynamic timeliness requires reasoning about it with some formal theory of uncertainty. Ordinary probability theory cannot deal with ignorance and paradoxical information. This book surveys some popular theories which can do so, and focuses on applying mathematical theories of evidence (i.e., Dempster-Shafer theory and its subsequent elaborations). The foundation introduced here has been successfully employed in a multiplicity of different application-specific real-time contexts having wickedly dynamic system models and core properties, where traditional static real-time perspectives and traditions were inadequate and counter-productive.

    N.B. There still are pages from the previous (c. 2008-2012) version of this site which I have not yet updated and integrated (or removed).

    Next: Introduction

    About Me

    E. Douglas Jensen is a well-known pioneer and thought leader in real-time and distributed real-time systems–especially dynamic ones. His professional accomplishments have been in Award-winning innova
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    Introduction (to the Preview) “Sometimes shifting your perspective is much better than being smart.” — Astro Teller, TED Talk This is a work-in-progress, highly condensed and less form
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