A technique for adaptive scheduling of soft real-time tasks

A number of multimedia and process control applications can take advantage from the ability to adapt soft real-time load to available computational capacity. This capability is required, for example, to react to changed operating conditions as well as to ensure graceful degradation of an application under transient overloads. In this paper, we illustrate a novel adaptive scheduling technique based on rate modulation of a set of periodic tasks in a range of admissible rates. By casting constraints on rate ranges in a linear programming formulation, several adaptation policies can be considered, along with additional constraints reflecting various application requirements. The paper investigates the effectiveness of rate modulation strategies both on simulated task sets and on real experiments.