Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control

TL;DR

This paper develops a minimax framework for finite-time queueing control analysis, introduces a Lyapunov-based scheduling policy that outperforms MaxWeight in finite time, and provides theoretical bounds and insights into scheduling policy performance.

Contribution

It presents the first finite-time performance analysis framework for queueing policies, introduces the LyapOpt policy, and compares its performance to classical MaxWeight.

Findings

LyapOpt achieves optimal finite-time performance in heavy traffic.

Minimax lower bounds on queue length are derived using Brownian coupling.

MaxWeight's finite-time performance depends suboptimally on system parameters.

Abstract

We introduce an original minimax framework for finite-time performance analysis in queueing control and propose a surprisingly simple Lyapunov-based scheduling policy with superior finite-time performance. The framework quantitatively characterizes how the expected total queue length scales with key system parameters, including the capacity of the scheduling set and the variability of arrivals and departures across queues. To our knowledge, this provides the first firm foundation for evaluating and comparing scheduling policies in the finite-time regime, including nonstationary settings, and shows that the proposed policy can provably and empirically outperform classical MaxWeight in finite time. Within this framework, we establish three main sets of results. First, we derive minimax lower bounds on the expected total queue length for parallel-queue scheduling via a novel Brownian coupling argument. Second, we propose a new policy, LyapOpt, which minimizes the full quadratic Lyapunov drift-capturing both first- and second-order terms-and achieves optimal finite-time performance in heavy traffic while retaining classical stability guarantees. Third, we identify a key limitation of the classical MaxWeight policy, which optimizes only the first-order drift: its finite-time performance depends suboptimally on system parameters, leading to substantially larger backlogs in explicitly characterized settings. Together, these results delineate the scope and limitations of classical drift-based scheduling and motivate new queueing-control methods with rigorous finite-time guarantees.