Digital Twin Driven Service Self-Healing With Graph Neural Networks in 6G Edge Networks-Reference-Cited by-同舟云学术

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Digital Twin Driven Service Self-Healing With Graph Neural Networks in 6G Edge Networks

Published:2023-11 Issue:11 Volume:41 Page:3607-3623
ISSN:0733-8716
Container-title:IEEE Journal on Selected Areas in Communications
language:
Short-container-title:IEEE J. Select. Areas Commun.

Author:

Yu Peng¹^ORCID,Zhang Junye¹^ORCID,Fang Honglin¹^ORCID,Li Wenjing¹^ORCID,Feng Lei¹^ORCID,Zhou Fanqin¹^ORCID,Xiao Pei²^ORCID,Guo Song³^ORCID

Affiliation:

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

2. Department of Wireless Communications, Institute for Communication Systems, Home of 5GIC and 6GIC, University of Surrey, GU2 7XH Surrey, Guildford, U.K

3. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

Funder

National Natural Science Foundation of China

BUPT Excellent Ph.D. Students Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/49/10297955/10234541.pdf?arnumber=10234541

Reference52 articles.

1. xNet: Improving Expressiveness and Granularity for Network Modeling with Graph Neural Networks

2. Knowledge-Defined Networking

3. Joint Task Partitioning and User Association for Latency Minimization in Mobile Edge Computing Networks

4. Mining frequent patterns without candidate generation

5. A (sub)graph isomorphism algorithm for matching large graphs

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