Energy-Efficient Online Service Migration in Edge Networks-Reference-Cited by-同舟云学术

Energy-Efficient Online Service Migration in Edge Networks

Published:2024-09-15 Issue:18 Volume:11 Page:29689-29708
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Li Jiangwei¹^ORCID,Zhao Deng²,Shi Zhensheng³,Meng Lin⁴^ORCID,Gaaloul Walid⁵^ORCID,Zhou Zhangbing²^ORCID

Affiliation:

1. School of Information Engineering, China University of Geosciences (Beijing), Beijing, China

2. School of Information Engineering, and Frontiers Science Center for Deep-Time Digital Earth, China University of Geosciences (Beijing), Beijing, China

3. Department of Shale Gas, Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, China

4. College of Science and Engineering, Ritsumeikan University, Kusatsu, Japan

5. Computer Science Department, TELECOM SudParis, Evry, France

Funder

?Deep-time Digital Earth? Science and Technology Leading Talents Team Funds for the Central Universities for the Frontiers Science Center for Deep-time Digital Earth, China University of Geosciences

the National Natural Science Foundation of China

China Geological Survey (CGS) work project: "Geoscience literature knowledge services and decision supporting."

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10660568/10540573.pdf?arnumber=10540573

Reference50 articles.

1. From Information Networking to Intelligence Networking: Motivations, Scenarios, and Challenges

2. Integrating Edge Intelligence and Blockchain: What, Why, and How

3. Service-Oriented Resource Allocation for Blockchain-Empowered Mobile Edge Computing

4. Design, monitoring, and testing of microservices systems: The practitioners’ perspective

5. Fine-Grained Performance and Cost Modeling and Optimization for FaaS Applications