Stochastic Analysis of Expected Schedulability for Real-Time Tasks on a Single Computing System

In this paper, we propose the expected schedulability to characterize the schedulability for the stochastic tasks on a single real-time computer processor. Our results show that the stochastic model has more flexibility to characterize the real-time tasks than the deterministic model. The expected schedulability is related to the real-time t at tasks arrival and may show that a sub-set of task would be scheduled at any given real-time interval. The numerical analysis based on our theoretic results is consistent with the simulation analysis. Both numerical and simulation results show that the tasks would be scheduled for real-time tasks in realtime systems if the traffic load is less than a specific value which is more than 69%, which was provided in some deterministic situations. This observation implies that the expected schedulability based on the stochastic model would provide a bigger threshold for the real-time tasks to be scheduled.