An Adaptive Fuzzy Based 2-Layered HRRN CPU Scheduler

Abstract

Fuzzy Based CPU scheduler becomes an emerging component of an operating system. It can handle the imprecise nature of parameters used in scheduler. This paper introduces an adaptive fuzzy based Highest Response Ratio Next CPU scheduler which is an extension of conventional CPU scheduler. Proposed scheduler works in 2 layers. At the first layer, a Fuzzy Inference System is defined which handles the uncertainties of parameters and at the second layer, an adaptive scheduling algorithm is used to schedule each task. Proposed scheduler intelligently generates the response ratio for each ready to run task which makes the system adaptive at run time. The work is compared with the conventional highest response ratio next scheduling and the existing fuzzy highest ratio next scheduling algorithms. Results validate the better performance of proposed scheduler. The proposed scheduler also provides comparable results with respect to shortest job first scheduling and shortest remaining task first scheduling algorithms.