Demonstrating Waffle: A Self-driving Grid Index
Summary: Waffle: a self-driving grid index for moving objects that automates grid partitioning, indexing and operational tuning to handle spatio-temporal mobility. Demonstrates architecture, workflow and user scenarios showing hands-off management and continuous performance improvement via automated adaptation. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Dalsu Choi
- 2. Hyunsik Yoon
- 3. Hyubjin Lee
- 4. Yon Dohn Chung
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 102 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049545203 |
| 183 | Automatic Database Management System Tuning Through Large-scale Machine Learning | 2017 | SIGMOD | 0.00036721403 |
| 514 | An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning | 2019 | SIGMOD | 0.0002124895 |
| 782 | QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning | 2019 | VLDB | 0.00016729063 |
| 1,827 | An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems | 2021 | VLDB | 0.00010390548 |
| 2,678 | Effectively Learning Spatial Indices | 2020 | VLDB | 8.3252088e-05 |
| 3,914 | A Demonstration of the OtterTune Automatic Database Management System Tuning Service | 2018 | VLDB | 6.6339644e-05 |
| 9,605 | Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System | 2022 | VLDB | 4.3177432e-05 |
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