CausalMesh: A Causal Cache for Stateful Serverless Computing
Stateful serverless workflows consist of multiple serverless functions that access state on a remote database. Developers sometimes add a cache layer between the serverless runtime and the database to improve I/O latency. However, in a serverless environment, functions in the same workflow may be scheduled to different nodes with different caches, which can cause non-intuitive anomalies. This paper presents CausalMesh, a novel approach to causally consistent caching in serverless computing. CausalMesh is the first cache system that supports coordination-free and abort-free read/write operations and read transactions when clients roam among multiple servers. CausalMesh also supports read-write transactional causal consistency in the presence of client roaming, but at the cost of abort-freedom. Our evaluation shows that CausalMesh has lower latency and higher throughput than existing proposals.
Authors
- Shuai Mu (ORCID: https://orcid.org/0000-0001-8244-2109)
- Sebastian Angel (ORCID: https://orcid.org/0000-0002-3798-5590)
- Haoran Zhang (ORCID: https://orcid.org/0000-0002-6883-1375)
- Vincent Liu (ORCID: https://orcid.org/0000-0003-1987-9521)
Institutions
- Stony Brook University (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Proceedings of the VLDB Endowment
- Published
- 2024-09-01
- DOI
- https://doi.org/10.14778/3704965.3704969
- Citations
- 1
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.78
Funders
- National Science Foundation