GAMPS: Compressing Multi Sensor Data by Grouping and Amplitude Scaling
Summary: GAMPS groups correlated sensor signals and scales amplitudes to meet per-signal L∞ error. It delivers polynomial-time O(alpha,beta) approximations and an index for querying compressed data; experiments show strong space savings with query support. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sorabh Gandhi
- 2. Suman Nath
- 3. Subhash Suri
- 4. Jie Liu
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,824 | Managing Massive Time Series Streams with Multi-Scale Compressed Trickles | 2009 | VLDB | 5.8947137e-05 |
| 11,133 | Scalable Model-Based Management of Massive High Frequency Wind Turbine Data with ModelarDB | 2024 | VLDB | 4.1945683e-05 |
| 12,342 | Enabling epsilon-Approximate Querying in Sensor Networks | 2009 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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