Thumbnail
Access Restriction
Subscribed

Author Browne, J. C. ♦ Sherman, Stephen ♦ Baskett, Forest
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Scheduling ♦ Multiprogramming ♦ Performance measurement ♦ Cpu scheduling ♦ Trace driven models
Abstract Microscopic level job stream data obtained in a production environment by an event-driven software probe is used to drive a model of a multiprogramming computer system. The CPU scheduling algorithm of the model is systematically varied. This technique, called trace-driven modeling, provides an accurate replica of a production environment for the testing of variations in the system. At the same time alterations in scheduling methods can be easily carried out in a controlled way with cause and effects relationships being isolated. The scheduling methods tested included the best possible and worst possible methods, the traditional methods of multiprogramming theory, round-robin, first-come-first-served, etc., and dynamic predictors. The relative and absolute performances of these scheduling methods are given. It is concluded that a successful CPU scheduling method must be preemptive and must prevent a given job from holding the CPU for too long a period.
Description Affiliation: Univ. of Texas at Austin, Austin (Sherman, Stephen; Baskett, Forest; Browne, J. C.)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 15
Issue Number 12
Page Count 7
Starting Page 1063
Ending Page 1069


Open content in new tab

   Open content in new tab
Source: ACM Digital Library