Joint DNN partitioning and resource allocation for completion rate maximization of delay-aware DNN inference tasks in wireless powered mobile edge computing-Reference-Cited by-同舟云学术

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Joint DNN partitioning and resource allocation for completion rate maximization of delay-aware DNN inference tasks in wireless powered mobile edge computing

Published:2023-09-20 Issue:6 Volume:16 Page:2865-2878
ISSN:1936-6442
Container-title:Peer-to-Peer Networking and Applications
language:en
Short-container-title:Peer-to-Peer Netw. Appl.

Author:

Tian Xianzhong,Xu Pengcheng,Shen Yifan,Shao Yuheng

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Link

https://link.springer.com/content/pdf/10.1007/s12083-023-01564-z.pdf

Reference23 articles.

1. Liu W, Wang Z, Liu X, Zeng N, Liu Y, Alsaadi FE (2017) A survey of deep neural network architectures and their applications. Neurocomputing 234:11–26

2. Cardoso VB, Oliveira AS, Forechi A, Azevedo P, Mutz FW, Oliveira-Santos T, Badue C, Souza AFD (2020) A large-scale mapping method based on deep neural networks applied to self-driving car localization, pp 1–8

3. Shah SH, Yaqoob I (2016) A survey: Internet of things (iot) technologies, applications and challenges. 2016 IEEE Smart Energy Grid Engineering (SEGE), pp 381–385

4. Sze V, Chen Y, Yang T, Emer JS (2017) Efficient processing of deep neural networks: A tutorial and survey. Proc IEEE 105(12):2295–2329

5. Roberts DA, Yaida S, Hanin B (2022) The principles of deep learning theory

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