Elastic task model for adaptive rate control

An increasing number of real time applications, related to multimedia and adaptive control systems, require greater flexibility than classical real time theory usually permits. We present a novel periodic task model, in which tasks' periods are treated as springs, with given elastic coefficients. Under this framework, periodic tasks can intentionally change their execution rate to provide different quality of service, and the other tasks can automatically adapt their periods to keep the system underloaded. The proposed model can also be used to handle overload conditions in a more flexible way, and provide a simple and efficient mechanism for controlling the quality of service of the system as a function of the current load.