Supriya Raheja1, Reena Dhadich2 and Smita Rajpal1, 1ITM University, India and 2Government Engg. College, India
ABSTRACT
In Round Robin CPU scheduling algorithm the main concern is with the size of time quantum and the increased waiting and turnaround time. Decision for these is usually based on parameters which are assumed to be precise. However, in many cases the values of these parameters are vague and imprecise. The performance of fuzzy logic depends upon the ability to deal with Linguistic variables. With this intent, this paper attempts to generate an Optimal Time Quantum dynamically based on the parameters which are treated as Linguistic variables. This paper also includes Mamdani Fuzzy Inference System using Trapezoidal membership function, results in LRRTQ Fuzzy Inference System. In this paper, we present an algorithm to improve the performance of round robin scheduling algorithm. Numerical analysis based on LRRTQ results on proposed algorithm show the improvement in the performance of the system by reducing unnecessary context switches and also by providing reasonable turnaround time.
KEYWORDS
CPU Scheduling, Round Robin (RR) Scheduling Algorithm, Time Quantum, Turnaround time, Fuzzy Inference System (FIS).
Original Source URL: https://airccse.org/journal/ijsc/papers/2112ijsc05.pdf
https://airccse.org/journal/ijsc/current2012.html
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