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Abstract

In this paper a rule-based fuzzy scheduling method is presented. Aim of this method is to handle the uncertainty and vagueness that characterize the complicated process of task scheduling. It uses fuzzy sets to describe both a task’s deadline and a task’s remaining execution time. The operation of the presented scheduling method is based on a rule-based reasoner that decides dynamically about the priority of the tasks that wait to be executed. This reasoner is triggered each time a change occurs (e.g. the execution of a task ends, a new task arrives etc.). It has been compared with Earlied Deadline First (EDF) scheduling algorithm. The results showed that the presented fuzzy scheduling method improves the scheduling process, since it minimizes both, the mean waiting time and the mean turnaround time.

Keywords

Task scheduling fuzzy logic rule-based fuzzy reasoner SRTF EDF

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Improving task scheduling by using a fuzzy reasoner

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