QoS-based management of multiple shared resource in dynamic real-time systems

Dynamic real-time systems require adaptive resource management to accommodate varying processing needs. We address the problem of resource management with multiple shared resources for soft real-time systems consisting of tasks that have discrete QoS settings that correspond to varying resource usage and varying utility. Given an amount of available resource, the problem is to provide on-line control of the tasks' QoS settings so as to optimize the overall system utility. We propose several heuristic algorithms that will be shown to be compatible with the requirements imposed by our control theoretical resource management framework: (1) By only making incremental adjustments to QoS settings as available resources change, they provide low run-time complexity, making them suitable for use in on-line resource managers. (2) Differences between actual utility and optimal utility do not accumulate over time, so there is no long-term degradation in performance. (3) The lower and upper bound on actual utility can be calculated dynamically based on current system conditions, and absolute bounds can be calculated statically in advance. (4) It is possible to respond to the actual resource possible, allowing all resources to be used and tolerating misspecification of task resource requirements