Communication-Oriented Model Fine-Tuning for Packet-Loss Resilient Distributed Inference Under Highly Lossy IoT Networks

Communication-Oriented Model Fine-Tuning for Packet-Loss Resilient Distributed Inference Under Highly Lossy IoT Networks

The distributed inference (DI) framework has gained traction as a technique for real-time applications empowered by cutting-edge deep machine learning (ML) on resource-constrained Internet of things (IoT) devices. In DI, computational tasks are offloaded from the IoT device to the edge server via lo...

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Bibliographic Details
Main Authors: Sohei Itahara, Takayuki Nishio, Yusuke Koda, Koji Yamamoto
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Distributed inference
communication-efficiency
machine learning
packet loss tolerant
delay-aware system
Online Access:https://ieeexplore.ieee.org/document/9705589/

Internet

https://ieeexplore.ieee.org/document/9705589/

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