No abstract

Mixed-criticality scheduling algorithms, which attempt to reclaim system capacity lost to worst-case execution time pessimism, seem to hold great promise for multicore real-time systems, where such loss is particularly severe. However, the unique nature of these algorithms gives rise to a number of major challenges for the would-be implementer. This paper describes the first implementation of a mixed-criticality scheduling framework on a multicore system. We experimentally evaluate design tradeoffs that arise when seeking to isolate tasks of different criticalities and to maintain overheads commensurate with a standard RTOS. We also evaluate a key property needed for such a system to be practical: that the system be robust to breaches of the optimistic execution-time assumptions used in mixed-criticality analysis.

The evolution of multicore platforms has led to much recent work on multiprocessor scheduling techniques for soft realtime workloads. However, end users routinely run such workloads atop general-purpose operating systems with seemingly good results, albeit typically on over-provisioned systems. This raises the question: when, if ever, is the use of an analysisbased scheduler actually warranted? In this paper, this question is addressed via a video-decoding case study in which a scheme based on the global earliest-deadline-first (G-EDF) algorithm was compared against Linux's CFS scheduler. In this study, the G-EDF-based scheme proved to be superior under heavy workloads in terms of several timing metrics, including jitter and deadline tardiness. Prior to discussing these results, an explanation of how existing G-EDF-related scheduling theory was applied to provision the studied system is given and various "mismatches" between theoretical assumptions and practice that were faced are discussed.