Feedback scheduling of power-aware soft real-time tasks

In this paper we propose an enerfy-based feedback control scheduling framework for power-aware soft real-time tasks executing in dynamic environments, where real-time parameters are not known a priori. We propose the use of a controller based on an Energy Savings Ratio, which allows higher energy savings when higher missed deadlines are allowed to ocurr. The scheduler uses the energy feedback to calculate the amount Of workload to be adjusted and provides the input for a variable voltage optimization algorithm (MA). The VVA algorithm is a greedy algorithm that adjusts the workload to optimize power consumption by computing a near optimal solution for the tasks's voltage/speed selection problem. Extensive sets of tests are executed to simulate the performance of our energy feedback scheduling power-aware architecture under overload and underload conditions. Simulation results show that the proposed architecture is capable of handling real-time tasks with unknown arrivals and execution times, and derive a system in which power savings are maximized.