On-line scheduling algorithm for real-time multiprocessor systems with ACO

The Ant Colony Optimization algorithms (ACO) are computational models inspired by the collective foraging behavior of ants. By looking at the strengths of ACO, they are the most appropriate for scheduling of tasks in soft real-time systems. In this paper, ACO based scheduling algorithm for real-time operating systems (RTOS) has been proposed. During simulation, results are obtained with periodic tasks, measured in terms of Success Ratio & Effective CPU Utilization and compared with Kotecha’s algorithm in the same environment. It has been observed that the proposed algorithm is equally optimal during underloaded conditions and it performs better during overloaded conditions.