Recent datacenter load balancing designs make full use of all available multiple paths to achieve high bisection bandwidth and support the increasing traffic demands. However, a multitude of uncertainties, such as congestion and asymmetry, easily leads to long tailed latencies for unlucky flows on bad paths. In this paper, we aim at adjusting the maximum number of multiple paths used by existing load balancing designs to achieve good tradeoff between the tailed latency and link utilization. Specifically, we propose a packet-level load balancing called scheme Adaptively Adjusting Concurrency (AAC) to spread packets across the multiple paths, which are adaptively selected according to path diversity. AAC is deployed at switch, without any modifications on end-hosts. The experimental results of NS2 simulation and Mininet implementation show that AAC significantly reduces the flow completion time by \(\sim\)21–56% over the state-of-the-art datacenter load balancing designs including MPTCP, LetFlow and RPS.

最近的数据中心负载平衡设计充分利用了所有可用的多条路径，以实现较高的二等分带宽并支持不断增长的流量需求。但是，大量的不确定性（例如拥塞和不对称）很容易导致长途延迟，导致不良路径上的运气不佳。在本文中，我们旨在调整现有负载平衡设计所使用的最大路径数，以在拖延的延迟和链路利用率之间取得良好的平衡。具体来说，我们提出了一种称为方案自适应调整并发性（AAC）的数据包级负载平衡，以将数据包分布在多个路径上，这些路径根据路径分集进行自适应选择。AAC部署在交换机上，无需在最终主机上进行任何修改。\（\ sim \）比最新的数据中心负载平衡设计（包括MPTCP，LetFlow和RPS ）高出21–56％。