Function as a Service for Edge Computing: Challenges and Solutions
The widespread adoption of mobile devices and large-scale deployment of edge IoT devices have ushered humanity into an era of intelligent interconnectivity. Currently, the computing architecture dominated by cloud data centers is increasingly struggling to meet the growing demand for edge computing services. As a result, the concept of edge computing has been proposed and widely studied in recent years. Meanwhile, Function as a Service (FaaS) is driving cloud computing service technologies toward more flexible and fine-grained models. By effectively combining edge computing with FaaS, it is possible to leverage the strengths of each, addressing the unique requirements of edge-intelligent applications, such as low latency, dependency on edge data, privacy protection, low-frequency requests, and traffic bursts. However, as research on this model is still in its early stages, this paper summarizes the latest research and analyzes the challenges and potential solutions faced by this architectural model. Specifically, the following tasks are carried out: 1) A brief review of the development status of edge computing and FaaS; 2) A discussion of the issues arising from introducing FaaS in the edge computing environment, identifying six key challenges for the future; 3) Proposing four possible solutions for FaaS applications in edge computing environments, based on the analysis of existing research and related work; 4) Listing four major open-source serverless frameworks and five leading edge serverless platform providers, along with their main features.
Authors
- Songling Tang (ORCID: https://orcid.org/0000-0002-3979-4261)
- Jialong Ding
- Congfeng Jiang (ORCID: https://orcid.org/0000-0003-3592-0328)
- Yufei Chen (ORCID: https://orcid.org/0000-0001-6648-4923)
- Yun Chen (ORCID: https://orcid.org/0000-0002-9934-9979)
- Junming Liu (ORCID: https://orcid.org/0000-0002-9301-0894)
Institutions
- Hangzhou Dianzi University (CN)
Publication Details
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1109/icctit64404.2024.10928463
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00