Work

DataFlower: Exploiting the Data-flow Paradigm for Serverless Workflow Orchestration

Year: 2023

Type: conference-paper

Abstract: Serverless computing that runs functions with auto-scaling is a popular task execution pattern in the cloud-native era. By connecting serverless functions into workflows, tenants can achieve complex functionality. Prior research adopts the control-flow paradigm to orchestrate a serverless workflow. However, the control-flow paradigm inherently results in long response latency, due to the heavy data persistence overhead, sequential resource usage, and late function triggering.

Source: ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)

DOI: 10.1145/3623278.3624755

Authors: Zijun Li, Chuhao Xu, Quan Chen, Jieru Zhao, Chen Chen, Minyi Guo

Institution: Shanghai Jiao Tong University

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: National Natural Science Foundation of China, Shanghai International Science and Technology

Awards: G2465329715, G2857700228, G3393564379, G7942366687