Combining Tasklevel and Systemlevel Scheduling Modes for Mixed Criticality Systems Different scheduling algorithms for mixed criticality systems have been recently proposed. The common denominator of these algorithms is to discard low critical tasks whenever high critical tasks are in lack of computation resources. This is achieved upon a switch of the scheduling mode from Normal to Critical. We distinguish two main categories of the algorithms: systemlevel mode switch and tasklevel mode switch. Systemlevel mode algorithms allow low criticality (LC) tasks to execute only in normal mode. Tasklevel mode switch algorithms enable to switch the mode of an individual high criticality task (HC), from low (LO) to high (HI), to obtain priority over all LC tasks. This paper investigates an online scheduling algorithm for mixedcriticality systems that supports dynamic mode switches for both task level and system level. When a HC task job overruns its LC budget, then only that particular job is switched to HI mode. If the job cannot be accommodated, then the system switches to Critical mode. To accommodate for resource availability of the HC jobs, the LC tasks are degraded by stretching their periods until the Critical mode exhibiting job complete its execution. The stretching will be carried out until the resource availability is met. We have mechanized and implemented the proposed algorithm using Uppaal. To study the efficiency of our scheduling algorithm, we examine a case study and compare our results to the state of the art algorithms.

FaultTolerant Online Scheduling Algorithms for CubeSats CubeSats are small satellites operating in harsh space environment. In order to ensure correct functionality on board despite faults, fault tolerant techniques taking into account spatial, time and energy constraints should be considered. This paper presents a softwarelevel solution taking advantage of several processors available on board. Two online scheduling algorithms are introduced and evaluated. The results show their performances and the tradeoff between the rejection rate and energy consumption. Last but not least, it is stated that ordering policies achieving low rejection rate when using the algorithm scheduling all tasks as aperiodic are the Earliest Deadline and Earliest Arrival Time. As for the algorithm treating arriving tasks as aperiodic or periodic tasks, the Minimum Slack ordering policy provides reasonable results.