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Peer-to-Peer Deep Learning for Beyond-5G IoT
May 7, 2024, 4:45 a.m. | Srinivasa Pranav, Jos\'e M. F. Moura
cs.LG updates on arXiv.org arxiv.org
Abstract: We present P2PL, a practical multi-device peer-to-peer deep learning algorithm that, unlike the federated learning paradigm, does not require coordination from edge servers or the cloud. This makes P2PL well-suited for the sheer scale of beyond-5G computing environments like smart cities that otherwise create range, latency, bandwidth, and single point of failure issues for federated approaches.
P2PL introduces max norm synchronization to catalyze training, retains on-device deep model training to preserve privacy, and leverages local …
abstract algorithm arxiv bandwidth beyond cities cloud computing create cs.dc cs.lg deep learning edge edge servers environments federated learning iot latency paradigm peer peer-to-peer practical scale servers smart smart cities type
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