Maximizing the Accrued Utility of an Isochronal Soft Real-Time System Using Genetic Algorithms

Many real-time systems are in fact isochronal, where both early and late responses are harmful to the system or lead to lower quality of service. Real-time task scheduling problems proved that are NP-hard problems. Therefore, it is necessary to apply a heuristic search strategy on these problems. In this paper, a multi-objective genetic algorithm is proposed for static task scheduling in non-overloaded isochronal soft real-time systems. Its objective is to maximize the total utility of jobs. Simulation results indicate that genetic algorithm could be a suitable heuristic search strategy for task scheduling in isochronal soft real-time systems.