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.

中文翻译：

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动态路径切换的轮盘赌轮平衡算法在多径数据中心网络中的应用

负载平衡是数据中心网络中的重要问题。基于小流的算法可以以细粒度平衡流量，并且不会遭受数据包错误排序的问题。但是它们的性能相当有限，或者需要额外的通信开销。在本文中，我们提出了一种称为动态轮盘赌轮（DRW）的本地负载感知算法。在DRW中，采用轮盘赌轮根据本地负载为小流量选择新路径。每个多径源均平衡了到其所有出口链路的通信量，而没有通信开销。而且，可以将小流的粒度从单个数据包动态调整为整个流。最后，针对链路或交换机故障的情况设计了容量聚合（CA）机制。我们从理论上证明DRW可以实现最佳的全局负载平衡。