SD-AETO: Service-Deployment-Enabled Adaptive Edge Task Offloading Scheme in MEC-Reference-Cited by-同舟云学术

SD-AETO: Service-Deployment-Enabled Adaptive Edge Task Offloading Scheme in MEC

Published:2023-11-01 Issue:21 Volume:10 Page:19296-19311
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Song Liangjun¹,Sun Gang²^ORCID,Yu Hongfang¹^ORCID,Guizani Mohsen³^ORCID

Affiliation:

1. Key Laboratory of Optical Fiber Sensing and Communications, Ministry of Education, University of Electronic Science and Technology of China, Chengdu, China

2. Key Laboratory of Optical Fiber Sensing and Communications, Ministry of Education, Agile and Intelligent Computing Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China

3. Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE

Funder

National Key Research and Development Program of China

PCL Future Greater-Bay Area Network Facilities for Large-Scale Experiments and Applications

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/ielx7/6488907/10288305/10140145.pdf?arnumber=10140145

Reference42 articles.

1. Edge Intelligence: Empowering Intelligence to the Edge of Network

2. Computation Offloading via Sinkhorn’s Matrix Scaling for Edge Services

3. Learning-Based Joint Optimization of Energy Delay and Privacy in Multiple-User Edge-Cloud Collaboration MEC Systems

4. Collaborate Edge and Cloud Computing With Distributed Deep Learning for Smart City Internet of Things

5. Federated Multiagent Actor–Critic Learning for Age Sensitive Mobile-Edge Computing