SRPT Scheduling Discipline in Many-Server Queues with Impatient Customers

The shortest-remaining-processing-time (SRPT) scheduling policy has been extensively studied, for more than 50 years, in single-server queues with infinitely patient jobs. Yet, much less is known about its performance in multiserver queues. In this paper, we present the first theoretical analysis of SRPT in multiserver queues with abandonment. In particular, we consider the [Formula: see text] queue and demonstrate that, in the many-sever overloaded regime, performance in the SRPT queue is equivalent, asymptotically in steady state, to a preemptive two-class priority queue where customers with short service times (below a threshold) are served without wait, and customers with long service times (above a threshold) eventually abandon without service. We prove that the SRPT discipline maximizes, asymptotically, the system throughput, among all scheduling disciplines. We also compare the performance of the SRPT policy to blind policies and study the effects of the patience-time and service-time distributions. This paper was accepted by Baris Ata, stochastic models & simulation.

Dynamic Scheduling of Multiclass Many-Server Queues with Abandonment: The Generalized cμ/h Rule

In “Dynamic Scheduling of Multiclass Many-Server Queues with Abandonment: The Generalized cμ/h Rule,” Long, Shimkin, Zhang, and Zhang propose three scheduling policies to cope with any general cost functions and general patience-time distributions. Their first contribution is to introduce the target-allocation policy, which assigns higher priority to customer classes with larger deviation from the desired allocation of the service capacity and prove its optimality for any general queue-length cost functions and patience-time distributions. The Gcμ/h rule, which extends the well-known Gcμ rule by taking abandonment into account, is shown to be optimal for the case of convex queue-length costs and nonincreasing hazard rates of patience. For the case of concave queue-length costs but nondecreasing hazard rates of patience, it is optimal to apply a fixed-priority policy, and a knapsack-like problem is developed to determine the optimal priority order efficiently.