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Releasing Cloud Databases from the Chains of Performance Prediction Models

Summary: Move from brittle query-latency predictors to ML that directly models monetary cost of provisioning and executing query workloads. Design an RL-based IaaS service that learns low-cost VM provisioning and query-dispatch policies for dynamic clouds; PoC validates feasibility. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
310
Venue
CIDR
Year
2017
Pagerank
6.4112736e-05
Overall Rank
4,987 | 65.79%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{marcus_cidr17,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '17},
        title = {{Releasing Cloud Databases from the Chains of Performance Prediction Models}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Marcus, Ryan and Papaemmanouil, Olga},
        year = {2017}
}

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