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RushMon: Real-time Isolation Anomalies Monitoring

Summary: RushMon: first real-time isolation anomalies monitor for high-throughput, low-isolation systems. It detects anomalies by counting cycles in the dependency graph, delivering ~1000x faster reporting with <1% overhead and enabling on-the-fly mitigation of incorrect results. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5640
Venue
SIGMOD
Year
2018
Pagerank
5.2014857e-05
Overall Rank
9,885 | 32.19%
DOI
10.1145/3183713.3196932

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{shang_sigmod18,
        title = {{RushMon: Real-time Isolation Anomalies Monitoring}},
        author = {Shang, Zechao and Yu, Jeffrey Xu and Elmore, Aaron J.},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3196932},
        url = {https://dl.acm.org/doi/10.1145/3183713.3196932},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
4,869 Epoch-based Commit and Replication in Distributed OLTP Databases 2021 VLDB 6.4709867e-05
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Outgoing Citations (Sorted by Pagerank)

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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