Papers › 007: Democratically Finding The Cause of Packet Drops
007: Democratically Finding The Cause of Packet Drops
Behnaz Arzani, Selim Ciraci, Luiz Chamon, Yibo Zhu, Hingqiang Liu, Jitu Padhye, Boon Thau Loo, Geoff Outhred
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur. We introduce 007, a lightweight, always-on diagnosis application that can find problematic links and also pinpoint problems for each TCP connection. 007 is completely contained within the end host. During its two month deployment in a tier-1 datacenter, it detected every problem found by previously deployed monitoring tools while also finding the sources of other problems previously undetected.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Anomaly Detection In Surveillance Videos | ShanghaiTech Weakly Supervised | Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection | AUC-ROC | 97.48 | #3 of 12 | Archive leaderboard | report |
| Continuous Control | DeepMind Cheetah Run (Images) | PlaNet | Return | 650 | #4 of 4 | Archive leaderboard | report |
| Language Modelling | 100 sleep nights of 8 caregivers | Gpt3 | 10% | 1 | #1 of 1 | Archive leaderboard | report |
| Node Classification | Cora (60%/20%/20% random splits) | GCN+JK | 1:1 Accuracy | 86.90 ± 1.51 | #23 of 33 | Archive leaderboard | report |
| Sign Language Recognition | RWTH-PHOENIX-Weather 2014 | SLRGAN | Word Error Rate (WER) | 23.4 | #16 of 22 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections