HarmonE couples a MAPE-K self-adaptation loop with MLOps to cut energy use by up to 54.5% while keeping 95% of predictive accuracy in a traffic-flow digital twin.
In: 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) (2019) 16 Bhatt et al
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HarmonE: A Self-Adaptive Approach to Architecting Sustainable MLOps
HarmonE couples a MAPE-K self-adaptation loop with MLOps to cut energy use by up to 54.5% while keeping 95% of predictive accuracy in a traffic-flow digital twin.