TY - CONF
T1 - AI-Powered Edge Computing Evolution for beyond 5G Communication Networks
AU - Kartsakli, Elli
AU - Perez-Romero, Jordi
AU - Sallent, Oriol
AU - Bartzoudis, Nikolaos
AU - Frascella, Valerio
AU - Mohalik, Swarup Kumar
AU - Metsch, Thiis
AU - Antonopoulos, Angelos
AU - Tuna, Ömer Faruk
AU - Deng, Yansha
AU - Tao, Xin
AU - Serrano, Maria A.
AU - Quiñones, Eduardo
N1 - Funding Information:
ACKNOWLEDGEMENT VERGE has received funding from the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101096034. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. The authors would like to thank the whole VERGE consortium for their contribution to shape the concepts, research challenges and solution approaches in VERGE.
Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Edge computing is a key enabling technology that is expected to play a crucial role in beyond 5G (B5G) and 6G communication networks. By bringing computation closer to where the data is generated, and leveraging Artificial Intelligence (AI) capabilities for advanced automation and orchestration, edge computing can enable a wide range of emerging applications with extreme requirements in terms of latency and computation, across multiple vertical domains. In this context, this paper first discusses the key technological challenges for the seamless integration of edge computing within B5G/6G and then presents a roadmap for the edge computing evolution, proposing a novel design approach for an open, intelligent, trustworthy, and distributed edge architecture.
AB - Edge computing is a key enabling technology that is expected to play a crucial role in beyond 5G (B5G) and 6G communication networks. By bringing computation closer to where the data is generated, and leveraging Artificial Intelligence (AI) capabilities for advanced automation and orchestration, edge computing can enable a wide range of emerging applications with extreme requirements in terms of latency and computation, across multiple vertical domains. In this context, this paper first discusses the key technological challenges for the seamless integration of edge computing within B5G/6G and then presents a roadmap for the edge computing evolution, proposing a novel design approach for an open, intelligent, trustworthy, and distributed edge architecture.
KW - AI/ML-based optimization
KW - B5G/6G evolution
KW - closed-loop automation
KW - Edge computing
KW - edge-cloud compute continuum
KW - security and trustworthiness
UR - http://www.scopus.com/inward/record.url?scp=85168419345&partnerID=8YFLogxK
U2 - 10.1109/EuCNC/6GSummit58263.2023.10188371
DO - 10.1109/EuCNC/6GSummit58263.2023.10188371
M3 - Paper
AN - SCOPUS:85168419345
SP - 478
EP - 483
T2 - 2023 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2023
Y2 - 6 June 2023 through 9 June 2023
ER -