Parallel Main-Memory Indexing for Moving-Object Query and Update Workloads
Summary: PGrid—an in-memory grid index for moving objects—exploits multi-core parallelism to handle high-rate workloads. Updates and queries share a single data structure, avoiding snapshots; hardware-assisted atomic updates with object-level copying implement non-divisible updates, delivering fresh results and near-linear scalability. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Darius Šidlauskas (Aalborg University)
- 2. Simonas Šaltenis (Aalborg University)
- 3. Christian S. Jensen (Aarhus University)
BibTeX Citation
@inproceedings{sidlauskas_sigmod12,
title = {{Parallel Main-Memory Indexing for Moving-Object Query and Update Workloads}},
author = {Šidlauskas, Darius and Šaltenis, Simonas and Jensen, Christian S.},
series = {{SIGMOD} '12},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2213836.2213842},
url = {https://dl.acm.org/doi/10.1145/2213836.2213842},
year = {2012}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,987 | Progressive Top-K Nearest Neighbors Search in Large Road Networks | 2020 | SIGMOD | 6.0183678e-05 |
| 7,070 | Indexing Methods for Moving Object Databases: Games and Other Applications | 2013 | SIGMOD | 5.7116663e-05 |
| 9,739 | Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System | 2022 | VLDB | 5.227679e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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