Awan, Muhammad AliBletsas, KonstantinosSouto, PedroÅkesson, BennyTovar, Eduardo2017-07-142017-07-1420171868-8969http://hdl.handle.net/10400.22/1007729th Euromicro Conference on Real-Time Systems (ECRTS 2017). 27 to 30, Jun, 2017, Main track, pp 18:1-18:21. Dubrovnik, Croatia.The design of mixed-criticality systems often involves painful tradeoffs between safety guarantees and performance. However, the use of more detailed architectural models in the design and analysis of scheduling arrangements for mixed-criticality systems can provide greater confidence in the analysis, but also opportunities for better performance. Motivated by this view, we propose an extension of Vestal’s model for mixed-criticality multicore systems that (i) accounts for the per-task partitioning of the last-level cache and (ii) supports the dynamic reassignment, for better schedulability, of cache portions initially reserved for lower-criticality tasks to the highercriticality tasks, when the system switches to high-criticality mode. To this model, we apply partitioned EDF scheduling with Ekberg and Yi’s deadline-scaling technique. Our schedulability analysis and scalefactor calculation is cognisant of the cache resources assigned to each task, by using WCET estimates that take into account these resources. It is hence able to leverage the dynamic reconfiguration of the cache partitioning, at mode change, for better performance, in terms of provable schedulability. We also propose heuristics for partitioning the cache in lowand high-criticality mode, that promote schedulability. Our experiments with synthetic task sets, indicate tangible improvements in schedulability compared to a baseline cache-aware arrangement where there is no redistribution of cache resources from low- to high-criticality tasks in the event of a mode change.engMixed criticality schedulingVestal modelDynamic redistribution of shared cacheShared last-level cache analysisCache-aware schedulingMixed-criticality Scheduling with Dynamic Redistribution of Shared Cacheconference object10.4230/LIPIcs.ECRTS.2017.18