Abstract
According to the conventional mixed-criticality (MC) system model, low-criticality tasks are completely discarded in high-criticality system mode. Allowing such loss of low-criticality tasks is controversial and not obviously necessary. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and fpEDF-VD scheduling. It is found that the two scheduling methods in VMPC retain the same speedup factors as in conventional MC systems. We develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux prototyping with consideration of overhead. The results show that schedulability degradation caused by continuing low-criticality task execution is often very small. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode. The prototyping results indicate that partitioned scheduling in VPMC outperforms the latest work based on fluid model.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 26th International Conference on Real-Time Networks and Systems, RTNS 2018 |
| Publisher | Association for Computing Machinery |
| Pages | 159-169 |
| Number of pages | 11 |
| ISBN (Electronic) | 9781450364638 |
| DOIs | |
| State | Published - Oct 10 2018 |
| Event | 26th International Conference on Real-Time Networks and Systems, RTNS 2018 - Poitiers, France Duration: Oct 10 2018 → Oct 12 2018 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Other
| Other | 26th International Conference on Real-Time Networks and Systems, RTNS 2018 |
|---|---|
| Country/Territory | France |
| City | Poitiers |
| Period | 10/10/18 → 10/12/18 |
Bibliographical note
Publisher Copyright:© 2018 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
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