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cs.DC2026
PRISM: Predictive Runtime In-place Scaling and Model Selection for Edge Microservices
Uwe Gropengießer, Thomas Reuter, Dominik Schön +3
Latency-sensitive edge AI services must balance strict deadlines, output quality, and limited compute and energy budgets. However, static CPU provisioning wastes resources because…
cs.DC2024
Apodotiko: Enabling Efficient Serverless Federated Learning in Heterogeneous Environments
Mohak Chadha, Alexander Jensen, Jianfeng Gu +2
Federated Learning (FL) is an emerging machine learning paradigm that enables the collaborative training of a shared global model across distributed clients while keeping the data…