Memory-Aware Feedback Scheduling of Control Tasks

Abstract

This paper presents the incorporation of an auto-tuning real-time garbage collector into a feedback-based on-line scheduling system. The studied feedback scheduler is designed to dynamically adjust the sampling periods of a set of controller tasks in order to maximize the overall control performance. In the suggested approach, the memory management overhead is made explicit and taken into account by the feedback scheduler when scheduling the tasks. It is also described how priorities for memory allocations can be used to control the allocation rates of the application threads in order to optimize the trade-off between memory and CPU time usage. A case study, comparing theoretical analysis and simulated results support the feasibility of the approach.