Heavy-Traffic Analysis of Queueing Systems with No Complete Resource Pooling

• 成果类型: Article; Early Access
• 署名作者: Lange, Daniela Andrea Hurtado; Maguluri, Siva Theja
• 署名单位: William & Mary; University System of Georgia; Georgia Institute of Technology
• 刊物名称: MATHEMATICS OF OPERATIONS RESEARCH
• ISSN/ISSBN: 0364-765X
• DOI: 10.1287/moor.2021.1248
• 发表日期: 2022
• 关键词: Asymptotic Optimality; parallel servers; performance; STABILITY; networks; policies; bounds; time

摘要

We study the heavy-traffic limit of the generalized switch operating under Max-Weight, without assuming that the complete resource pooling condition is satisfied and allowing for correlated arrivals. The main contribution of this paper is the steady-state mean of linear combinations of queue lengths in heavy traffic. We showcase the generality of our result by presenting various stochastic networks as corollaries, each of which is a contribution by itself. In particular, we study the input-queued switch with correlated arrivals, and we show that, if the state space collapses to a full-dimensional subspace, the correlation among the arrival processes does not matter in heavy traffic. We exemplify this last case with a parallel-server system, an .V-system, and an ad hoc wireless network. Whereas these results are obtained using the drift method, we additionally present a negative result showing a limitation of the drift method. We show that it is not possible to obtain the individual queue lengths using the drift method with polynomial test functions. We do this by presenting an alternate view of the drift method in terms of a system of linear equations, and we use this system of equations to obtain bounds on arbitrary linear combinations of the queue lengths.