AnTi-MiCS: Analytical Framework for Bounding Time in Embedded Mixed-Criticality Systems

TL;DR

This paper introduces AnTi-MiCS and MulTi-MiCS, analytical frameworks for determining low WCETs in embedded mixed-criticality systems, enhancing QoS and utilization efficiency through design-time analysis and multiple WCETs.

Contribution

It proposes novel analytical methods for low WCET determination, including handling bimodal distributions, to improve system performance in mixed-criticality environments.

Findings

QoS improved by 30.27% on average

Utilization waste reduced by 35.89%

MulTi-MiCS outperforms AnTi-MiCS in QoS and waste reduction

Abstract

In Mixed-Criticality (MC) systems, although the high Worst-Case Execution Time (WCET) serves as a conservative upper bound representing the task's maximum execution time under all conditions, obtaining a low WCET is essential for representing realistic executions and improving utilization and Quality-of-Service (QoS). Nevertheless, determining appropriate low WCET(s) for lower-criticality (LO) modes poses a significant challenge. Opting for a very low value of this WCET enhances processor utilization by scheduling more tasks in LO mode. Conversely, employing a larger WCET ensures fewer mode switches, thereby enhancing QoS, albeit at the cost of processor utilization. This paper proposes an analytical approach, AnTi-MiCS, to determine the appropriate low WCET through design-time analysis of task executions. In some cases, a single low WCET may not be adequate to capture large variations in the execution time distribution, for example, in scenarios like bimodal distributions. Therefore, we further propose a scalable approach, MulTi-MiCS, to compute multiple appropriate low WCETs. This approach exploits the temporal correlation between subsequent inputs presented to the application. Experimental results, conducted on a real platform with embedded real-time benchmarks, demonstrate the efficacy of our proposed scheme, in which QoS is improved by 30.27% on average while reducing utilization waste by 35.89%, compared to existing approaches. Besides, MulTi-MiCS improves QoS by 6.41% compared to AnTi-MiCS while reducing utilization waste by 8.23%.