Mutable Protection Domains: Towards a Component-Based System for Dependable and Predictable Computing

  • Authors:
  • Gabriel Parmer;Richard West

  • Affiliations:
  • -;-

  • Venue:
  • RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
  • Year:
  • 2007

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Abstract

The increasing complexity of software poses significant challenges for real-time and embedded systems beyond those based purely on timeliness. With embedded sys- tems and applications running on everything from mobile phones, PDAs, to automobiles, aircraft and beyond, an emerging challenge is to ensure both the functional and tim- ing correctness of complex software. We argue that static analysis of software is insufficient to verify the safety of all possible control flow interactions. Likewise, a static sys- tem structure upon which software can be isolated in sepa- rate protection domains, thereby defining immutable bound- aries between system and application-level code, is too in- flexible to the challenges faced by real-time applications with explicit timing requirements. This paper, therefore, in- vestigates a concept called "mutable protection domains" that supports the notion of hardware-adaptable isolation boundaries between software components. In this way, a system can be dynamically reconfigured to maximize soft- ware fault isolation, increasing dependability, while guar- anteeing various tasks are executed according to specific time constraints. Using a series of simulations on multi- dimensional, multiple-choice knapsack problems, we show how various heuristics compare in their ability to rapidly reorganize the fault isolation boundaries of a component- based system, to ensure resource constraints while simulta- neously maximizing isolation benefit. Our ssh oneshot algorithm offers a promising approach to address system dynamics, including changing component invocation pat- terns, changing execution times, and mispredictions in iso- lation costs due to factors such as caching. This material is based upon work supported by the National Science Foundation under Grant Numbers 0615153 and 0720464. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.