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Asymptotic optimality of switched control policies in a simple parallel server system under an extended heavy traffic condition

Rami Atar, Eyal Castiel, Martin I. Reiman

Research output: Contribution to journalArticlepeer-review

Abstract

This paper studies a two-class, two-server parallel server system under the recently introduced extended heavy traffic condition, which states that the underlying “static allocation” linear program (LP) is critical, but does not require that it has a unique solution. The main result is the construction of policies that asymptotically achieve previously proved a lower bound, on an expected discounted linear combination of diffusion- scaled queue lengths and are therefore asymptotically optimal (AO). Each extreme point solution to the LP determines a control mode—that is, a set of activities (class-server pairs) that are operational. When there are multiple solutions, these modes can be selected dynamically. It is shown that the number of modes required for AO is either one or two. In the latter case, there is a switching point in the (normalized) workload domain, characterized in terms of a free boundary problem. Our policies are defined by identifying pairs of elementary policies and switching between them at this switching point. They provide the first example in the heavy traffic literature where weak limits under an AO policy are given by a diffusion process where both the drift and diffusion coefficients are discontinuous.

Original languageEnglish
Pages (from-to)403-454
Number of pages52
JournalStochastic Systems
Volume14
Issue number4
DOIs
StatePublished - Dec 2024

Keywords

  • decomposable service rates
  • diffusion with discontinuous coefficients
  • dynamic graph of basic activities
  • extended heavy traffic condition
  • parallel server systems
  • switched control systems

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

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