Dynamic Quantum based Genetic Round Robin Algorithm

The performance of CPU is essentially depends on the scheduling algorithms. These algorithms provide a schedule for execution of processes waiting in ready queue. There are various scheduling algorithms; Round Robin is one of them. The performance of Round Robin algorithm is majorly depends on the quantum, generally which is static for all processes. There is not any standard way to decide the quantum. The larger quantum maximizes the waiting time and the smaller one increases the overhead of context switching among the processes. In order to improve the performance, the quantum can be dynamically selected for all iterations, instead of keeping it static. We implement Genetic Approach based Round Robin Algorithm with dynamic quantum. Genetic algorithm is evolutionary technique which finds optimal solutions for NP hard problems. We present comparison of three algorithms: Round Robin with static quantum, Round Robin with dynamic quantum and Genetic algorithm based Round Robin with dynamic quantum.