A Fine-Grained End-to-End Latency Optimization Framework for Wireless Collaborative Inference-Reference-Cited by-同舟云学术

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A Fine-Grained End-to-End Latency Optimization Framework for Wireless Collaborative Inference

Published:2023 Issue: Volume: Page:1-1
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Mu Lei¹^ORCID,Li Zhonghui²,Xiao Wei³,Zhang Ruilin⁴,Wang Peng¹,Liu Tao¹,Min Geyong⁵^ORCID,Li Keqin⁶^ORCID

Affiliation:

1. School of Computer Science and Engineering, Southwest Minzu University, Chengdu, China

2. School of Intelligent Engineering, Hubei Enshi College, Enshi, China

3. Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary

4. School of Business, The University of Auckland, Auckland, New Zealand

5. Department of Computer Science, University of Exeter, Exeter, U.K.

6. Department of Computer Science, State University of New York, New Paltz, New York, USA

Funder

Sichuan Science and Technology Program

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/6702522/10227294.pdf?arnumber=10227294

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. RCIF: Toward Robust Distributed DNN Collaborative Inference Under Highly Lossy IoT Networks;IEEE Internet of Things Journal;2024-08-01

2. Enhanced Wireless Communication Optimization with Neural Networks, Proximal Policy Optimization and Edge Computing for Latency and Energy Efficiency;International Journal of Electrical and Electronics Research;2024-06-30

3. Optimal Topology of Vision Transformer for Real-Time Video Action Recognition in an End-To-End Cloud Solution;Machine Learning and Knowledge Extraction;2023-09-29

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