A genetic algorithm for scheduling tasks in a real-time distributed system

Real time systems must often handle several independent periodic macro tasks, each one represented by a general task graph, including communications and precedence constraints. The implementation of such applications on a distributed system communicating via a bus, requires task assignment and scheduling as well as the taking into account of the communication delays. As periodicity implies macro task deadlines, the problem of finding a feasible schedule is critical. The paper addresses this NP hard problem resolution, by using a genetic algorithm under offline and non preemptive scheduling assumptions. The algorithm performance is evaluated on a large simulation set, and compared to classical list based algorithms, a simulated annealing algorithm and a specific clustering algorithm.