Feedback-based resource management for multi-threaded applications

Reconciling the constraint of guaranteeing to always meet deadlines with the optimization objective of reducing waste of computing capacity lies at the heart of a large body of research on real-time systems. Most approaches to doing so require the application designer to specify a deeper characterization of the workload (and perhaps extensive profiling of its run-time behavior), which then enables shaping the resource assignment to the application. In practice, such approaches are weak as they load the designer with the heavy duty of a detailed workload characterization. We seek approaches for reducing the waste of computing resources for recurrent real-time workloads in the absence of such additional characterization, by monitoring the minimal information that needs to be observable about the run-time behavior of a real-time system: its response time. We propose two resource control strategies to assign resources: one based on binary-exponential search and the other, on principles of control. Both approaches are compared against the clairvoyant scenario in which the average/typical behavior is known. Via an extensive simulation, we show that both techniques are useful approaches to reducing resource computation while meeting hard deadlines.