EVALUATION OF CPU SCHEDULING ALGORITHM WITH GENETIC APPROACH

Amit Gupta

Vol. 1, Jan-Dec 2015

Page Number: 23-31

Abstract:

There are many factors that affecting the efficiency of data processing systems. Understanding the operating system performance is a big issue. Operating system performance issues commonly involve process management, memory management, and scheduling. In computer System, Processor scheduling divides a computer processor's work between multiple programs so that it is continually switching from one opened application to another. This gives the appearance that the computer is running a number of different programs simultaneously as the whole process are very fast. Our study is an effort to develop an algorithm (genetic algorithm based) for obtaining optimal solution or near to optimal schedules for CPU Scheduling Problems with minimum computation effort even for large sized problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. In this paper we compare the result of average waiting time of general algorithms with the genetic algorithm

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