计算机科学
计算机网络
工作量
网络数据包
负载平衡(电力)
网络拥塞
分组交换
流量控制(数据)
绩效改进
实时计算
分布式计算
操作系统
网格
运营管理
几何学
数学
经济
作者
Qingyu Shi,Fang Wang,Dan Feng
标识
DOI:10.1109/tnsm.2020.2990868
摘要
Datacenter network load balancing schemes handle network traffic generated by massive different applications. Some packet-based or flowlet-based schemes capture traffic bursts for load balancing. But frequent rerouting within a flow can mix ACKs belonging to different paths in congestion control protocols, which adversely affects flow rate control. Besides, performance optimization effect of flowlet-based schemes may be less noticeable under smoother workloads. And several packet-based mechanisms implemented at end hosts can proactively reroute congested flows based on flow status even under a smooth workload, but fail to improve performance with the bursty nature of traffic. Therefore, existing schemes cannot adapt to different burst levels of dynamic traffic in datacenter networks and still have significant performance flaws in some ways. This paper proposes IntFlow, a novel load balancing scheme that integrates end-host based per-packet monitoring of flow status with flowlet switching in programable switches. IntFlow proactively reroutes flows experiencing network congestion or failures and avoids doing flowlet switching for small flows with high sending rate. IntFlow can provide excellent performance under both high burst and smooth workloads. Finally experimental results show IntFlow achieves up to 32% and 28% better performance than CONGA and Hermes under asymmetries, respectively.
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