Stationary Performance Analysis of Grishechkin Processor-Sharing Queues: An Integral Equation Approach

TL;DR

This paper derives solutions for the stationary performance metrics of a class of generalized processor-sharing queues using integral equations and transforms, providing insights into various scheduling policies.

Contribution

It introduces a method to solve the integral equation for performance metrics and applies it to multiple well-known scheduling policies.

Findings

Derived explicit solutions for performance metrics.

Provided approximations for density functions.

Unified analysis of several scheduling policies.

Abstract

We compute the stationary performance metrics of a single server $M^X/G/1$ queue under a class of generalized processor-sharing scheduling policies that are proposed by Grishechkin. This class of processor-sharing policies allow service capacities to be allocated to jobs based on the amount of service they attained. In [11], Grishechkin derives an integral equation that is satisfied by the Laplace transform of the stationary performance metrics under these policies. Our main focus in this paper is to derive the solution to this integral equation. This is achieved through a series of transforms that convert the integral equation into a more tractable form, then solve it. Then we derive approximations to the density functions of the performance metrics through inverting the Laplace transforms. In the last part of the paper, we apply our results to some well-known scheduling policies that are either a special case of the Grishechkin processor-sharing policies or can be treated as the limits of a sequence Grishechkin processor-sharing policies. These examples include the egalitarian processor-sharing policy, the discriminatory processor-sharing policy, shortest residual processing time first rule, foreground-background policy and the time function scheduling policy.