On the optimization of performance of time-sharing systems by simulation

Abstract

A simulation model of a time-sharing system with a finite noncontiguous store and an infinite auxiliary store is used to study the variation of system parameters such as store size, number of jobs allowed to execute simultaneously, job-scheduling algorithm, etc. The effects of these variations on a measure of system performance is used to ascertain which of the parameters controllable by the job-scheduling algorithm, including the scheduling itself, require optimization, and which of the parameters not normally controllable by the scheduling algorithm have a marked effect on system performance. System performance is based upon the mean cost of delay to all jobs processed. It is shown that significant improvements in the measure of system performance can be obtained by using variable time-slice techniques and by selecting the optimum round-robin cycle time. It appears that these features would benefit from optimization whereas other parameters controllable by the scheduling algorithm affect system performance in a predictable manner and would not benefit from optimization. Features not normally under the control of the scheduling algorithm can also have a marked effect on the measure of performance; in particular, supervisor overheads, the size of the store, and the speed of the CPU. A comparison is made between the results of the simulation model and two analytical equations for quantum-oriented nonpreemptive time-sharing systems. The comparison is found to be very favorable.