Robust Real-Time System Resource Management Using Feedback

Real-time computing is an enabling technology for many current and future application areas. Many future generations real-time systems are expected to be highly dynamic and operate in fault-prone on-deterministic environments under strict timing constraints. Therefore, these systems need to be robust while delivering high performance. This motivates the need for robust resource management techniques that dynamically address real-time requirements and provide graceful degradation in the presence of uncertainty. Despite the significant body of results in resource management in real-time systems, most of them are based on

``open-loop'' strategies which are effective when the workload can be accurately modeled. These schemes are inadequate for many real world problems wherein the workload cannot be accurately modeled. Thus, there is a need for efficient architectures for resource management where predictable performance guarantees

can be obtained in the presence of uncertainty.

Feedback control theory has been central to modeling systems operating in uncertain environments. In the past few decades, this theory has made impressive strides in this direction. Correct adaptation as illustrated by feedback control theory will yield significant dividends with respect to robustness. This research focuses on developing a robust resource management framework for real-time systems employing feedback control

strategies.