TRIM: An Efficient Framework for Exact Eccentricity Computation on Large-Scale Graphs
Summary: TRIM computes exact all-vertex eccentricities at scale using vertex dominance to prune redundant BFSs, a safe termination rule, and traversal merging. It delivers up to 100× speedups over prior bounding methods on graphs with 100M vertices. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Dian Ouyang (Guangdong University of Technology)
- 2. Jiajie Lin (Guangdong University of Technology)
- 3. Wentao Li (University of Leicester)
- 4. Fan Zhang (Guangdong University of Technology)
- 5. Jianye Yang (Guangdong University of Technology)
- 6. Xi Luo (Guangdong University of Technology)
BibTeX Citation
@article{ouyang_vldb26,
title = {{TRIM: An Efficient Framework for Exact Eccentricity Computation on Large-Scale Graphs}},
author = {Ouyang, Dian and Lin, Jiajie and Li, Wentao and Zhang, Fan and Yang, Jianye and Luo, Xi},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {4},
pages = {644--656},
doi = {10.14778/3785297.3785306},
url = {https://doi.org/10.14778/3785297.3785306},
year = {2026}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,403 | Scaling Up Distance Labeling on Graphs with Core-Periphery Properties | 2020 | SIGMOD | 6.7229209e-05 |
| 10,101 | On Scalable Computation of Graph Eccentricities | 2022 | SIGMOD | 5.1488731e-05 |
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