FleetIO: Managing Multi-Tenant Cloud Storage with Multi-Agent Reinforcement Learning
Cloud platforms have been virtualizing storage devices like flash-based solid-state drives (SSDs) to make effective use of storage resources. They enable either software-isolated instance or hardware-isolated instance for facilitating the storage sharing between multi-tenant applications. However, for decades, they have to combat the fundamental tussle between the performance isolation and resource utilization. They suffer from either long tail latency caused by weak isolation or low storage utilization caused by strong isolation.
Authors
- Jian Huang (ORCID: https://orcid.org/0000-0002-1125-671X)
- Jichuan Chang (ORCID: https://orcid.org/0000-0002-1896-3644)
- Daixuan Li (ORCID: https://orcid.org/0009-0008-1996-7939)
- Marc Snir (ORCID: https://orcid.org/0000-0002-3504-2468)
- Jinghan Sun (ORCID: https://orcid.org/0000-0001-7785-2971)
- Benjamin Reidys (ORCID: https://orcid.org/0009-0002-6185-2250)
Institutions
- Google (United States) (US)
- Urbana University (US)
Publication Details
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1145/3669940.3707229
- Citations
- 4
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 12.98