DEAL: Decremental Energy-Aware Learning in a Federated System
@article{Zou2021DEALDE, title={DEAL: Decremental Energy-Aware Learning in a Federated System}, author={Wenting Zou and Li Li and Zichen Xu and Chengzhong Xu}, journal={ArXiv}, year={2021}, volume={abs/2102.03051} }
Federated learning struggles with their heavy energy footprints on battery-powered devices. The learning process keeps all devices awake while draining expensive battery power to train a shared model collaboratively, yet it may still leak sensitive personal information. Traditional energy management techniques in system kernel mode can force the training device entering low power states, but it may violate the SLO of the collaborative learning. To address the conflict between learning SLO and…
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