Adaptive Scheduling Algorithm for Real-Time Operating System

EDF (Earliest Deadline First) has been proved to be optimal scheduling algorithm for single processor real-time operating systems when the systems are preemptive and underloaded. The limitation of this algorithm is, its performance decreases exponentially when system becomes slightly overloaded. Authors have already proved ability of ACO (Ant Colony Optimization) based scheduling algorithm for real-time operating system which is optimal during underloaded condition and it gives outstanding results in overloaded condition. The limitation of this algorithm is, it takes more time for execution compared to EDF algorithm. In this paper, an adaptive scheduling algorithm is proposed which is combination of both of these algorithms. Basically the new algorithm uses EDF algorithm but when the system becomes overloaded, it will switch to ACO based scheduling algorithm. Again, when the overload disappears, the system will switch to EDF algorithm. Therefore, the proposed algorithm takes the advantages of both algorithms and overcomes the limitations of each other. The proposed algorithm along with EDF algorithm and ACO based scheduling algorithm, is simulated for real-time system and the results are obtained. The performance is measured in terms of Success Ratio and Effective CPU Utilization. Execution Time taken by each scheduling algorithm is also measured. From analysis and experiments it reveals that the proposed algorithm is fast as well as very efficient in both underloaded and overloaded conditions.