Resource adaptations with servers for hard real-time systems

Many real-time applications are designed to work in different operating modes each characterized by different functionality and resource demands. With each mode change, resource demands of applications change, and static resource reservations may not be feasible anymore. Dynamic environments where applications may be added and removed online also need to adapt their resource reservations. In such scenarios, resource reconfigurations are needed for changing the resource reservations during runtime and achieve better resource allocations. There are a lot of results in the scientific literature of how to find the optimal amount of resources needed by an application in the different operating modes, or how an application can perform safe mode transitions. However, the problem of resource reconfigurations for systems with reservations has not been addressed. A resource scheduler should be reconfigured online in such a way that it still guarantees a certain amount of resources during the reconfiguration process, otherwise applications may miss deadlines. The paper proposes a framework for scheduling real-time applications through scheduling servers that provide resource reservations, and algorithms for changing the resource reservations online while still guaranteeing the feasibility of the system and the schedulability of applications. The framework analysis is integrated into a well-known modular performance analysis paradigm based on Real-Time Calculus. The results are illustrated with examples and a case study.