This paper presents a novel methodology to develop scheduling algorithms. The scheduling problem is phrased as a control problem, and control-theoretical techniques are used to design a scheduling algorithm that meets specific requirements. Unlike most approaches to feedback scheduling, where a controller integrates a "basic" scheduling algorithm and dynamically tunes its parameters and hence its performances, our methodology essentially reduces the design of a scheduling algorithm to the synthesis of a controller that closes the feedback loop. This approach allows the re-use of control-theoretical techniques to design efficient scheduling algorithms; it frames and solves the scheduling problem in a general setting; and it can naturally tackle certain peculiar requirements such as robustness and dynamic performance tuning. A few experiments demonstrate the feasibility of the approach on a real-time benchmark.
In @cite_15 , the controller adjusts the reservation time to within an upper bound given by the most frequently activated task. The model of the plant is a continuous-time system whose variables record the queuing time of tasks. The effectiveness of the method proposed is validated through simulations.
@cite_15
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This paper presents an approach to adaptive CPU scheduling for dynamic real-time systems using control-theoretic methods. Mathematical models are developed that form the basis for the design of controllers that optimize a certain performance measure. Simulation results are presented to show the efficacy of our approach.