Two classes of effective heuristics for time value functions based scheduling

In real-time computing system each task is associated with a function (time value function TVF) whose value at time t gives the award that the system receives if the corresponding task is achieved by this time. The authors investigate the NP-hard scheduling problem which consists in maximizing the sum of these awards. First on a theoretical point of view, they define an optimal decomposition : the set of the tasks to be scheduled is divided into a ranked collection of subsets so that an optimal scheduling has to respect the ranks of subsets. They also introduce two classes of polynomial scheduling algorithms which provide sequences respecting this optimal decomposition. On a practical point of view, simulation results show that these algorithms yield optimal or nearly optimal sequences in many cases.<>