Toward Supporting XR Services: Architecture and Enablers

Author:

Taleb Tarik1ORCID,Boudi Abderrahmane2ORCID,Rosa Luis3,Cordeiro Luis3,Theodoropoulos Theodoros4,Tserpes Konstantinos4ORCID,Dazzi Patrizio5ORCID,Protopsaltis Antonis I.6ORCID,Li Richard7

Affiliation:

1. Faculty of Information Technology and Electrical Engineer, University of Oulu, Oulu, Finland

2. Communications and Networking Department, ICTFicial Oy, Espoo, Finland

3. Research and Development Department, OneSource, Coimbra, Portugal

4. Department of Informatics and Telematics, Harokopio University, Kallithea, Greece

5. Department of Computer Science, University of Pisa, Pisa, Italy

6. Department of Electrical and Computer Engineering, University of Western Macedonia, Kozani, Greece

7. Network Technologies Lab, Futurewei, Santa Clara, CA, USA

Funder

European Union’s Horizon 2020 Research and Innovation Programme through the CHARITY

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

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3. Digital Twin and Artificial Intelligence-Empowered Panoramic Video Streaming: Reducing Transmission Latency in the Extended Reality-Assisted Vehicular Metaverse;IEEE Vehicular Technology Magazine;2023-12

4. Security in Cloud-Native Services: A Survey;Journal of Cybersecurity and Privacy;2023-10-26

5. Multi-Agent Deep Reinforcement Learning for Weighted Multi-Path Routing;Proceedings of the 3rd Workshop on Flexible Resource and Application Management on the Edge;2023-08-14

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