A Semi-Partitioned Model for Mixed Criticality Systems
Hao Xu and Alan Burns
Many Mixed Criticality algorithms have been developed with an assumption thatlower criticality-level tasks may be abandoned in orderto guarantee the schedulability of higher-criticality tasks when the criticality level of the system changes.But it is valuable to explore means by which all of the tasks remain schedulable through these criticality level changes.This paper introduces a semi-partitioned model for a multi-core platform thatallows all of the tasks to remain schedulable ifonly a bounded number of cores increase their criticality level. In such a model,some lower-criticality tasks are allowed to migrate instead of being abandoned.Detailed response time analysis for this model is derived.This paper also introduces possible approaches for establishing migration routes.Together with related previous work, an appropriate semi-partitioned model for mixedcriticality systems hosted on multi-core platforms is recommended.
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BibTex Entry
@article{Xu_2019,
author = {Hao Xu and Alan Burns},
day = {1},
doi = {10.1016/j.jss.2019.01.015},
issn = {0164-1212},
journal = {Journal of Systems and Software},
keywords = {Real-time, Mixed Criticality},
language = {English},
month = {4},
pages = {51--63},
publisher = {Elsevier},
pure_url = {https://pure.york.ac.uk/portal/en/publications/a-semipartitioned-model-for-mixed-criticality-systems(6f5816d0-7808-465e-8e73-f5438ebb8ac5).html},
title = {A Semi-Partitioned Model for Mixed Criticality Systems},
url = {https://doi.org/10.1016%2Fj.jss.2019.01.015},
volume = {150},
year = {2019}
}