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 manage-ment with multiple shared resources for soft real-time systems consisting of tasks that have discrete QoS set-tings 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 util-ity. We propose several heuristic algorithms that will be shown to be compatible with the requirements im-posed by our control theoretical resource management framework: (1) By only making incremental adjust-ments to QoS settings as available resources change, they provide low run-time complexity, making them suitable for use in on-line resource managers (2) Dif-ferences 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 mis-specification of task resource requirements.