3 papers
cs.LG2020
ResiliNet: Failure-Resilient Inference in Distributed Neural Networks
Ashkan Yousefpour, Brian Q. Nguyen, Siddartha Devic +5
Federated Learning aims to train distributed deep models without sharing the raw data with the centralized server. Similarly, in distributed inference of neural networks, by partit…
cs.NI2019
Guardians of the Deep Fog: Failure-Resilient DNN Inference from Edge to Cloud
Ashkan Yousefpour, Siddartha Devic, Brian Q. Nguyen +4
Partitioning and distributing deep neural networks (DNNs) over physical nodes such as edge, fog, or cloud nodes, could enhance sensor fusion, and reduce bandwidth and inference lat…
cs.NI2019
DeepPR: Progressive Recovery for Interdependent VNFs with Deep Reinforcement Learning
Genya Ishigaki, Siddartha Devic, Riti Gour +1
The increasing reliance upon cloud services entails more flexible networks that are realized by virtualized network equipment and functions. When such advanced network systems face…