一句话：揭示 FaaS 中传统 master-worker 工作流执行的调度与数据移动瓶颈，并引出 FaaSFlow 优化方案。
FaaS 通过在容器中运行函数实现细粒度资源共享，数据依赖函数需按预定义逻辑组成 serverless workflow。论文调研发现，传统 master-worker 工作流执行架构在无服务器场景下表现不佳：主节点侧的工作流调度模式会先触发函数再分配到 worker，带来显著开销；worker 之间的数据移动也会降低吞吐。针对这些问题，FaaSFlow 面向 FaaS 改进工作流执行（标题与摘要暗示其目标是实现高效执行），但摘要未给出具体方法与量化评估结果。
Serverless computing (Function-as-a-Service) provides fine-grain resource sharing by running functions (or Lambdas) in containers. Data-dependent functions are required to be invoked following a pre-defined logic, which is known as serverless workflows. However, our investigation shows that the traditional master-worker based workflow execution architecture performs poorly in serverless context. One significant overhead results from the master-side workflow schedule pattern, with which the functions are triggered in the master node and assigned to worker nodes for execution. Besides, the data movement between workers also reduces the throughput.
@inproceedings{LiLGCCZG22,
title = {FaaSFlow: enable efficient workflow execution for function-as-a-service},
author = {Zijun Li and Yushi Liu and Linsong Guo and Quan Chen and Jiagan Cheng and Wenli Zheng and Minyi Guo},
booktitle = {ASPLOS},
year = {2022},
doi = {10.1145/3503222.3507717}
}