具有有限灵活性的排队系统拓扑

J. Tsitsiklis, Kuang Xu
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引用次数: 44

摘要

我们研究了一个多服务器模型,其中有n个灵活的服务器和rn个队列,通过一个固定的二部图连接,其中的灵活性水平由队列的平均度d(n)来捕获。数据中心的内容复制应用程序、呼叫中心的基于技能的路由和灵活的供应链是我们的主要动机。我们关注的是系统大小n趋于无穷大,而整体流量强度保持固定的缩放机制。我们表明,即使在非常有限的灵活性(d(n) ln)下,也可以共同实现大容量区域(鲁棒性)和减少排队延迟(性能)。特别是,当d(n) gg ln n时,一组基于随机图的互连拓扑(高概率)能够稳定所有允许的到达率向量(在有界支持假设下),同时确保队列延迟减少,为ln n/ d(n)阶,为n->∞。我们的分析集中在一类新的基于虚拟队列的调度策略上,这些策略依赖于连接图上动态构造的部分匹配。
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Queueing system topologies with limited flexibility
We study a multi-server model with n flexible servers and rn queues, connected through a fixed bipartite graph, where the level of flexibility is captured by the average degree, d(n), of the queues. Applications in content replication in data centers, skill-based routing in call centers, and flexible supply chains are among our main motivations. We focus on the scaling regime where the system size n tends to infinity, while the overall traffic intensity stays fixed. We show that a large capacity region (robustness) and diminishing queueing delay (performance) are jointly achievable even under very limited flexibility (d(n) l n). In particular, when d(n) gg ln n , a family of random-graph-based interconnection topologies is (with high probability) capable of stabilizing all admissible arrival rate vectors (under a bounded support assumption), while simultaneously ensuring a diminishing queueing delay, of order ln n/ d(n), as n-> ∞. Our analysis is centered around a new class of virtual-queue-based scheduling policies that rely on dynamically constructed partial matchings on the connectivity graph.
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