Learning-Aided Heuristics Design for Storage System
Summary: Learning-aided heuristic design for storage systems using DRL to synthesize white-box, interpretable strategies. Outperforms default and handcrafted policies in production resource allocation; DRL insights rendered as human-readable rules. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yingtian Tang (Huawei; University of Pennsylvania)
- 2. Han Lu (Huawei; Shanghai Jiao Tong University)
- 3. Xijun Li (Huawei; University of Science and Technology Beijing)
- 4. Lei Chen (Huawei)
- 5. Mingxuan Yuan (Huawei)
- 6. Jia Zeng (Huawei)
BibTeX Citation
@inproceedings{tang_sigmod21,
title = {{Learning-Aided Heuristics Design for Storage System}},
author = {Tang, Yingtian and Lu, Han and Li, Xijun and Chen, Lei and Yuan, Mingxuan and Zeng, Jia},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457554},
url = {https://dl.acm.org/doi/10.1145/3448016.3457554},
year = {2021}
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