Compensating Adaptive Mixed Criticality Scheduling

TY - GEN

T1 - Compensating Adaptive Mixed Criticality Scheduling

AU - Davis, Robert Ian

AU - Burns, Alan

AU - Bate, Iain

N1 - © 2022 Association for Computing Machinery. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2022/6/7

Y1 - 2022/6/7

N2 - The majority of prior academic research into mixed criticality systems assumes that if high-criticality tasks continue to execute beyond the execution time limits at which they would normally finish, then further workload due to low-criticality tasks may be dropped in order to ensure that the high-criticality tasks can still meet their deadlines. Industry, however, takes a different view of the importance of low-criticality tasks, with many practical systems unable to tolerate the abandonment of such tasks. In this paper, we address the challenge of supporting genuinely graceful degradation in mixed criticality systems, thus avoiding the abandonment problem. We explore the Compensating Adaptive Mixed Criticality (C-AMC) scheduling scheme. C-AMC ensures that both high- and low-criticality tasks meet their deadlines in both normal and degraded modes. Under C-AMC, jobs of low-criticality tasks, released in degraded mode, execute imprecise versions that provide essential functionality and outputs of sufficient quality, while also reducing the overall workload. This compensates, at least in part, for the overload due to the abnormal behavior of high-criticality tasks. C-AMC is based on fixed-priority preemptive scheduling and hence provides a viable migration path along which industry can make an evolutionary transition from current practice.

AB - The majority of prior academic research into mixed criticality systems assumes that if high-criticality tasks continue to execute beyond the execution time limits at which they would normally finish, then further workload due to low-criticality tasks may be dropped in order to ensure that the high-criticality tasks can still meet their deadlines. Industry, however, takes a different view of the importance of low-criticality tasks, with many practical systems unable to tolerate the abandonment of such tasks. In this paper, we address the challenge of supporting genuinely graceful degradation in mixed criticality systems, thus avoiding the abandonment problem. We explore the Compensating Adaptive Mixed Criticality (C-AMC) scheduling scheme. C-AMC ensures that both high- and low-criticality tasks meet their deadlines in both normal and degraded modes. Under C-AMC, jobs of low-criticality tasks, released in degraded mode, execute imprecise versions that provide essential functionality and outputs of sufficient quality, while also reducing the overall workload. This compensates, at least in part, for the overload due to the abnormal behavior of high-criticality tasks. C-AMC is based on fixed-priority preemptive scheduling and hence provides a viable migration path along which industry can make an evolutionary transition from current practice.

KW - Real-Time

KW - Schedulability Analysis

KW - Fixed Priority

KW - Mixed Criticality

UR - https://www-users.cs.york.ac.uk/~robdavis/papers/CAMCRTNS2022.pdf

UR - https://www.youtube.com/watch?v=geUVGqPJkYk

UR - https://www-users.cs.york.ac.uk/~robdavis/

U2 - 10.1145/3534879.3534895

DO - 10.1145/3534879.3534895

M3 - Conference contribution

AN - SCOPUS:85132424284

SN - 9781450396509

T3 - ACM International Conference Proceeding Series

SP - 81

EP - 93

BT - RTNS 2022 - Proceedings of the 30th International Conference on Real-Time Networks and Systems

A2 - Abdeddaïm, Yasmina

A2 - Cucu-Grosjean, Liliana

A2 - Nelissen, Geoffrey

A2 - Pautet, Laurent

PB - ACM

T2 - 30th International Conference on Real-Time Networks and Systems, RTNS 2022

Y2 - 7 June 2022 through 8 June 2022

ER -