iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases
Summary: iBTune automates per-instance buffer tuning in cloud DBs under a fixed memory budget. It uses similarity-based miss-ratio inference and a pairwise deep neural network to bound response time, enabling memory reduction across 10k OLTP instances. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jian Tan (Alibaba)
- 2. Tieying Zhang (Alibaba)
- 3. Feifei Li (Alibaba)
- 4. Jie Chen (Alibaba)
- 5. Qixing Zheng (Alibaba)
- 6. Ping Zhang (Alibaba)
- 7. Honglin Qiao (Alibaba)
- 8. Yue Shi (Alibaba)
- 9. Wei Cao (Alibaba)
- 10. Rui Zhang (Alibaba)
BibTeX Citation
@article{tan_vldb19,
title = {{iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases}},
author = {Tan, Jian and Zhang, Tieying and Li, Feifei and Chen, Jie and Zheng, Qixing and Zhang, Ping and Qiao, Honglin and Shi, Yue and Cao, Wei and Zhang, Rui},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {10},
pages = {1221--1234},
doi = {10.14778/3339490.3339503},
url = {https://doi.org/10.14778/3339490.3339503},
year = {2019}
}
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|---|---|---|---|---|
| 1 | 4,788 | iTuned: A Tool for Configuring and Visualizing Database Parameters | 2010 | SIGMOD |
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| 8 | 334 | An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning | 2019 | SIGMOD |
| 9 | 4,011 | Towards Dynamic and Safe Configuration Tuning for Cloud Databases | 2022 | SIGMOD |
| 10 | 3,116 | ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases | 2021 | SIGMOD |