Abstract—Students taking their first course in the Principles of Operating Systems usually have textbooks as their only resource material. In order to assist them to better understand the basic concepts of process scheduling algorithms as well as their respective advantages and disadvantages, there is the need for a tool to show experimentally the behaviour of these algorithms through comparative performance studies and analyses. A lot of commercial and educational software programs are available but each has its drawbacks ranging from high cost of acquisition for the commercial systems and non-flexibility for the educational systems. Others find their place between these two extremes such as non-availability and inefficiency. This paper presents the implementation of a lightweight, simple, robust and flexible tool for the comparative and experimental study of two existing as well as an innovative probabilistic CPU process scheduling algorithm, using Average Waiting Time (AWT) and Average Turn-around Time (ATT) as the criteria for performance evaluation. The tool was used to simulate the three algorithms using eight datasets representing different scenarios of processes with their burst times and respective locations on a virtual queue. The results showed the robustness of this software, especially for academic and experimental use, as well as proving the desirability and efficiency of the probabilistic algorithm over the other existing techniques.

Index Terms—Process scheduling algorithms, probabilistic algorithm, average waiting time; average turn-around time.

F. Anifowose was with the Information and Computer Science department when this experiment was carried out. He is a Research Engineerat the Center for Petroleum and Minerals, King Fahd University of Petroleum and Minerals, Saudi Arabia (e-mail: anifowo@kfupm.edu.sa).

Cite: Fatai Adesina Anifowose, Member, IACSIT, "MySIM: A Light-Weight Tool for the Simulation of Probabilistic CPU Process Scheduling Algorithm," International Journal of Computer and Electrical Engineering vol. 4, no. 1, pp. 25-31, 2012.