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Three metrics for stochastic networks: Capacity, queue-size and complexity

机译:随机网络的三个指标:容量,队列大小和复杂性

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We consider a class of constrained queuing network called switched networks, important sub-class of the stochastic processing network (cf. Harrison (2000)), in which there are constraints on which queues can be served simultaneously. Such networks have served as effective models for understanding various types of dynamic resource allocation problems arising in communication networks like the Internet, computer architecture, manufacturing, etc. In such systems, a scheduling policy is required to make resource allocation decisions in terms of which queues to serve at each time subject to constraints. The performance of the system is crucially determined by the scheduling policy. The performance of such scheduling policies, measured with respect to the following three metrics is of utmost importance: (a) capacity, (b) induced queue-sizes or latency, and (c) complexity of the implementation of the policy. Ideally, one is interested in determining the trade-offs achievable between these metrics characterized through the pareto performance boundary. In this note, we shall summarize the state-of-art along with recent progresses towards this somewhat ambitious program.
机译:我们考虑一类称为交换网络的约束排队网络,它是随机处理网络的重要子类(cf. Harrison(2000)),其中存在可以同时服务队列的约束。这样的网络已经成为理解诸如Internet,计算机体系结构,制造等通信网络中出现的各种类型的动态资源分配问题的有效模型。在这样的系统中,需要一种调度策略来根据哪个队列做出资源分配决策。每次都受到限制。系统的性能由调度策略决定。相对于以下三个指标衡量的此类调度策略的性能至关重要:(a)容量,(b)引起的队列大小或延迟,以及(c)策略实施的复杂性。理想情况下,人们有兴趣确定在通过pareto性能边界表征的这些指标之间可以实现的取舍。在本说明中,我们将总结最新技术以及该宏伟计划的最新进展。

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