通过包级并行性加速容器覆盖网络中的包处理

Jiaxin Lei, Manish Munikar, Hui Lu, J. Rao
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引用次数: 1

摘要

覆盖网络作为事实上的网络虚拟化技术,用于在分布式容器之间提供连接。尽管在构建自定义私有容器网络方面具有灵活性,但与物理网络(即本机网络)相比,覆盖网络会导致显著的性能损失。其根源在于叠加网络中包含了多个网络处理阶段,延长了网络处理路径,使CPU内核过载。在本文中,我们提出了mFlow,一种新颖的数据包转向方法来并行化网络流的内核内数据路径。mFlow利用内核网络堆栈中的包级并行性,将同一流的数据包分成多个微流,这些微流可以在多个内核上并行处理。mFlow设计了新的、通用的流分裂机制,同时以很小的开销保持有序的数据包传递。我们对微基准测试和实际应用的评估都证明了mFlow的有效性,性能显著提高——例如,与普通覆盖网络相比,TCP吞吐量提高了81%,UDP吞吐量提高了139%。mFlow甚至实现了比本机更高的TCP吞吐量(例如,29.8 vs. 26.6 Gbps)。
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Accelerating Packet Processing in Container Overlay Networks via Packet-level Parallelism
Overlay networks serve as the de facto network virtualization technique for providing connectivity among distributed containers. Despite the flexibility in building customized private container networks, overlay networks incur significant performance loss compared to physical networks (i.e., the native). The culprit lies in the inclusion of multiple network processing stages in overlay networks, which prolongs the network processing path and overloads CPU cores. In this paper, we propose mFlow, a novel packet steering approach to parallelize the in-kernel data path of network flows. mFlow exploits packet-level parallelism in the kernel network stack by splitting the packets of the same flow into multiple micro-flows, which can be processed in parallel on multiple cores. mFlow devises new, generic mechanisms for flow splitting while preserving in-order packet delivery with little overhead. Our evaluation with both micro-benchmarks and real-world applications demonstrates the effectiveness of mFlow, with significantly improved performance – e.g., by 81% in TCP throughput and 139% in UDP compared to vanilla overlay networks. mFlow even achieved higher TCP throughput than the native (e.g., 29.8 vs. 26.6 Gbps).
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