Hard real-time scheduling for low-energy using stochastic data and DVS processors

The work presented in this paper addresses scheduling for reduced energy of hard real-time tasks with fixed priorities assigned in a rate monotonic or deadline monotonic manner. The approach we describe can be exclusively implemented in the RTOS. It targets energy consumption reduction by using both on-line and off-line decisions, taken both at task level and at task-set level. We consider sets of independent tasks running on processors with dynamic voltage supplies (DVS). Taking into account the real behavior of a realtime system, which is often better than the worst case, our methods employ stochastic data to derive energy efficient schedules. The experimental results show that our approach achieves more important energy reductions than other policies from the same class.