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Throughput Unfairness in Dragonfly Networks under Realistic Traffic Patterns

机译:实际流量模式下蜻蜓网络的吞吐量不公平

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Dragonfly networks have a two-level hierarchical arrangement of the network routers, and allow for a competitive cost-performance solution in large systems. Non-minimal adaptive routing is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Throughput unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. Previous works have demonstrated the presence of throughput unfairness in Dragonflies under certain adversarial traffic patterns, and proposed different alternatives to effectively combat such effect. In this paper we introduce a new traffic pattern denoted adversarial consecutive (ADVc), which portrays a real use case, and evaluate its impact on network performance and throughput fairness. This traffic pattern is the most adversarial in terms of network fairness. Our evaluations, both with or without transit-over-injection priority, show that global misrouting policies do not properly alleviate this problem. Therefore, explicit fairness mechanisms are required for these networks.
机译:蜻蜓网络具有网络路由器的两级分层结构,并可以在大型系统中提供具有竞争力的性价比解决方案。采用非最小自适应路由可充分利用路径分集并提高对抗性流量模式下的性能。吞吐量不公平会阻止在网络节点之间平衡使用资源,并严重降低在受影响的节点上运行的任何应用程序的性能。先前的工作证明了在某些对抗性交通模式下蜻蜓中存在吞吐量不公平的现象,并提出了不同的替代方法来有效地对抗这种影响。在本文中,我们介绍了一种称为对抗性连续(ADVc)的新流量模式,该流量模式描绘了一个实际用例,并评估了其对网络性能和吞吐量公平性的影响。就网络公平性而言,这种流量模式是最具对抗性的。我们的评估(无论是否具有优先注入过境)都表明,全球错误路由策略无法适当缓解这一问题。因此,这些网络需要明确的公平机制。

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