Roulette Wheel Balancing Algorithm With Dynamic Flowlet Switching for Multipath Datacenter Networks
Roulette Wheel Balancing Algorithm With Dynamic Flowlet Switching for Multipath Datacenter Networks
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DOI：
10.1109/tnet.2021.3051995
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发表时间：
2021-04
期刊：
影响因子：
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通讯作者：
Fujie Fan;Hangyu Meng;Bing Hu;K. Yeung;Zhifeng Zhao
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文献类型：
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作者：
Fujie Fan;Hangyu Meng;Bing Hu;K. Yeung;Zhifeng Zhao
负载平衡是数据中心网络中的一个重要问题。基于小流的算法可以细粒度地平衡流量，并且不会遭受分组误排序问题。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，我们提出了一个本地负载感知算法称为动态轮盘赌轮（DRW）。在DRW中，采用轮盘赌的方式，根据局部负载为小流选择新的路径。每个多路径源在没有通信开销的情况下平衡到其所有出口链路的流量。此外，小流的粒度可以从单个数据包到整个流进行动态调整。最后，容量聚合（CA）机制的情况下，链路或交换机故障的设计。从理论上证明了DRW能够实现全局最优负载均衡。仿真结果还表明，DRW提供了几乎最好的延迟性能和最小的数据包乱序比例的总体上所有现有的小流交换算法。
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.