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Title: A semi-partitioned model for scheduling mixed criticality multi-core systems
Author: Xu, Hao
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2017
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Many Mixed Criticality scheduling algorithms have been developed with an assumption that lower criticality level tasks may be abandoned to 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 throughout criticality level changes. This thesis introduces a semi-partitioned model which allows all of the tasks to remain schedulable if only a bounded number of cores increase their criticality levels. In such a model, some lower criticality tasks are allowed to migrate instead of being abandoned. Different possible semi-partitioned approaches are proposed and analysed in this thesis. It is concluded from the experiments results that the semi-partitioned algorithm provides improved schedulability and performance of multi-core mixed criticality systems while enables all tasks to keep executing in the majority of scenarios.
Supervisor: Burns, Alan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available