Quality-assuring scheduling-using stochastic behavior to improve resource utilization

We present a unified model for admission and scheduling, applicable for various active resources such as CPU or disk to assure a requested quality in situations of temporary overload. The model allows us to predict and control the behavior of applications based on given quality requirements. It uses the variations in the execution time, i.e., the time any active resource is needed We split resource requirements into a mandatory part which must be available and an optional part which should be available as often as possible but at least with a certain percentage. In combination with a given distribution for the execution time we can move away from worst-case reservations and drastically reduce the amount of reserved resources for applications which can tolerate occasional deadline misses. This increases the number of admittable applications. For example, with negligible loss of quality our system can admit more than two times the disk bandwidth than a system based on the worst-case. Finally, we validated the predictions of our model by measurements using a prototype real-time system and observed a high accuracy between predicted and measured values.