Auto-Tuning with Reinforcement Learning for Permissioned Blockchain Systems
Summary: Athena: an auto-tuner for Hyperledger Fabric using a novel PB‑MADDPG multi‑agent RL to optimize heterogeneous, distributed node parameters. By selecting high‑impact knobs, Athena yields up to 470% throughput and 75% latency improvements on a 12-peer/7-orderer Fabric, competitive with CDBTune/Qtune/ResTune. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Mingxuan Li (Chinese Academy of Sciences; People's Public Security University of China; University of Chinese Academy of Sciences)
- 2. Yazhe Wang (Zhongguancun Laboratory)
- 3. Shuai Ma (Beihang University)
- 4. Chao Liu (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
- 5. Dongdong Huo (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
- 6. Yu Wang (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
- 7. Zhen Xu (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
BibTeX Citation
@article{li_vldb23,
title = {{Auto-Tuning with Reinforcement Learning for Permissioned Blockchain Systems}},
author = {Li, Mingxuan and Wang, Yazhe and Ma, Shuai and Liu, Chao and Huo, Dongdong and Wang, Yu and Xu, Zhen},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {5},
pages = {1000--1012},
doi = {10.14778/3579075.3579076},
url = {https://doi.org/10.14778/3579075.3579076},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,707 | Refiner: A Reliable Incentive-Driven Federated Learning System Powered by Blockchain | 2021 | VLDB |
| 2 | 11,649 | Efficient Deterministic Concurrency Control Under Practical Isolation Levels | 2021 | SIGMOD |
| 3 | 1,020 | Blurring the Lines between Blockchains and Database Systems: the Case of Hyperledger Fabric | 2019 | SIGMOD |
| 4 | 8,917 | A Blockchain System for Clustered Federated Learning with Peer-to-Peer Knowledge Transfer | 2024 | VLDB |
| 5 | 4,339 | NeuChain: A Fast Permissioned Blockchain System with Deterministic Ordering | 2022 | VLDB |
| 6 | 11,808 | Scalable, Resilient, and Configurable Permissioned Blockchain Fabric | 2020 | VLDB |
| 7 | 11,436 | AdaChain: A Learned Adaptive Blockchain | 2023 | VLDB |
| 8 | 4,510 | Building High Throughput Permissioned Blockchain Fabrics: Challenges and Opportunities | 2020 | VLDB |
| 9 | 11,382 | How To Optimize My Blockchain? A Multi-Level Recommendation Approach | 2023 | SIGMOD |
| 10 | 11,210 | Towards Full Stack Adaptivity in Permissioned Blockchains | 2024 | VLDB |