Genetic Algorithm Based Adaptive Scheduling Algorithm for Real Time Operating Systems

In this paper novel technique for CPU scheduling in real time operating systems by using genetic algorithm (GA) is proposed. Proposed adaptive algorithm is a combination of existing dynamic priority driven algorithm i.e. Earliest Deadline First (EDF) and new genetic algorithm (GA) based scheduling algorithm. First we have developed GA based scheduling algorithm and tested it during both under loaded and overloaded condition. Initially, in underloaded condition EDF is used for scheduling and in overloaded condition system will change to a GA based scheduling algorithm .Thus our Adaptive algorithm uses the strong features of both algorithms and overcome their drawbacks. We have simulated, proposed adaptive algorithm along with both EDF and GA based algorithms for real time systems. %Success Rate and %Effective CPU Utilization are used as performance measuring criteria for all these 3 algorithms. The evaluation of results and comparison of our proposed adaptive CPU scheduling algorithm with EDF algorithm shows that the proposed adaptive algorithm is optimal and efficient during underloaded as well as overloaded situations compared to EDF