Abstract
It is well known, in queueing theory, that the system performance is greatly influenced by scheduling policy. No universal optimum scheduling strategy exists in systems where individual customer service demands are not known a priori. However, if the distribution of job times is known, then the residual time (expected time remaining for a job), based on the service it has already received, can be calculated. Our particular research contribution is in exploring the use of this function to enhance system performance by increasing the probability that a job will meet its deadline. In a detailed discrete event simulation, we have tested many different distributions with a wide range of C2 and shapes, as well as for single and dual processor system. Results of four distributions are reported here. We compare with RR and FCFS, and find that in all distributions studied our algorithm performs best. In the study of the use of two slow servers versus one fast server, we have discovered that they provide comparable performance, and in a few cases the double server system does better.
Highlights
There have been innumerable papers written on how to optimize performance in queueing systems
The proposed Residual Time Based (RTB) algorithm has been evaluated through discrete event simulation under various task arrival rates and task service time distributions
A four stage Hyper Erlangian with C2 10 The distributions were selected to give a wide variety of coefficient of variation, C2. This would yield a wide variety of mean system time, but with the same deadline
Summary
There have been innumerable papers written on how to optimize performance in queueing systems. For instance, the mean and variance, (the expectation, or mean, of the deviation squared of the variable from its expected value or mean) over all customers might be known, even though the time needed by a particular customer is not known until that customer is finished. Within each of these categories there are many possible goals. The goal might be to minimize the system time, as in job processing in computer systems, or minimize the waiting time, as in setting up telecommunication links. Both of these would be useless in situations where there are critical
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