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Roulette Wheel Balancing Algorithm With Dynamic Flowlet Switching for Multipath Datacenter Networks

机译:Roulette Wheen Balancing算法具有用于多径数据中心网络的动态流程

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Load balance is an important issue in datacenter networks. The flowlet-based algorithms can balance the traffic with fine granularity and does not suffer the packet mis-sequencing problem. But their performances are rather limited or require extra communication overhead. In this paper, we propose a local load-aware algorithm called Dynamic Roulette Wheel (DRW). In DRW, the roulette wheel is adopted to select a new path for the flowlet according to the local load. Each source of multipath balances the traffic to all its egress links without the communication overhead. Moreover, the granularity of flowlet can be dynamically tuned from a single packet to the whole flow. Finally, the Capacity Aggregation (CA) mechanism is designed for the case of link or switch failure. We prove in theory that DRW can achieve the optimal global load balancing. The simulation results also show that DRW provides almost the best delay performance and the least packet out-of-order proportion overall among all existing flowlet switching algorithms.
机译:负载余额是数据中心网络中的一个重要问题。基于流量的算法可以平衡流量以细粒度,并且不会遭受数据包错误测序问题。但他们的表演相当有限或需要额外的沟通开销。在本文中,我们提出了一种称为动态轮盘赌车轮(DRW)的本地负载感知算法。在DRW中,采用轮盘赌轮为局部负载选择流量的新路径。多径源余额将流量余额到所有出口链接的流量,而无需通信开销。此外,可以从单个分组动态地调谐流程的粒度到整个流程。最后,为链路或切换故障的情况设计了容量聚合(CA)机制。我们证明DRW可以实现最佳的全球负载平衡。仿真结果还表明,DRW在所有现有流式切换算法中提供了几乎最佳的延迟性能和最小的数据包超出订单。

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