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Bifrost: Analysis and Optimization of Network I/O Tax in Confidential Virtual Machines

Dingji Li, Zeyu Mi, Chenhui Ji, Yifan Tan, Binyu Zang, Haibing Guan, Haibo Chen

2023Year
31Citations
11Top-tier citations

Abstract

Existing confidential VMs (CVMs) experience notable network performance overhead compared to traditional VMs. We present the first thorough performance analysis of various network-intensive applications in CVMs and find that the CVM-IO tax, which mainly comprises the bounce buffer mechanism and the packet processing in CVMs, has a significant impact on network I/O performance. Specifically, the CVM-IO tax squeezes out virtual CPU (vCPU) resources of performance-critical application workloads and may occupy more than 50% of CPU cycles. To minimize the CVM-IO tax, this paper proposes Bifrost, a novel para-virtualized I/O design that 1) eliminates the I/O payload bouncing tax by removing redundant encryption and 2) reduces the packet processing tax via pre-receiver packet reassembly, while still ensuring the same level of security guarantees. We have implemented a Bifrost prototype with only minor modifications to the guest Linux kernel and the userspace network I/O backend. Evaluation results on both AMD and Intel servers demonstrate that Bifrost significantly improves the performance of I/Ointensive applications in CVMs, and even outperforms the traditional VM by up to 21.50%.

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