A state-based model for runtime resource reservation for component-based applications

Predictable execution enforcement for applications with highly and arbitrarily fluctuating resource usage requires runtime resource management. Correct runtime predictions regarding resource usage of individual components allows making proper resource reservations, enabling a better resource management of the component-based applications. This work presents a state-based resource usage model for a component, in which states represent CPU utilization intervals. This resource model is intended for a resourceaware component framework where it will be used to determine the quality of resource reservation. For this purpose, the model offers two metrics: failure rate, which measures the fraction of the reservation periods for which the reserved budget was insufficient, and resource waste, which measures unused budget.To illustrate the model, we apply it to a family of reservation prediction strategies and validate the outcome by means of a series of experiments in which we measure the resource utilization of two video components. The latter requires a method for monitoring resource states which is also presented, analyzed and validated in this paper. Keywords: runtime resource management, component-based applications, resource model, resource usage, resource predictio