EnTurbo: Accelerate Confidential Serverless Computing via Parallelizing Enclave Startup Procedure
Yifan Zhu, Peinan Li, Yunkai Bai, Yubiao Huang, Shiwen Wang, Xingbin Wang, Dan Meng, Rui Hou
Abstract
Serverless computing has gained widespread attention, and Trusted Execution Environments (TEEs) are well-suited for safeguarding user privacy. However, the additional startup procedure introduced by TEEs imposes considerable performance overhead on confidential serverless workloads. This paper introduces a novel parallelized enclave startup design, EnTurbo, which eliminates the integrity dependence of the enclave startup procedure, accelerating it while ensuring its security. Additionally, EnTurbo parallelizes the measurement procedure, enabling multi-thread measurement for acceleration with provable security. We evaluate EnTurbo by running confidential serverless workloads on SGX simulation mode. Results show that EnTurbo effectively speeds up enclave serverless by 1.42x-6.48x (SGXv1) and 1.33x-3.76x (SGXv2).
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