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Demo: EdgeRIC: Delivering Realtime RAN Intelligence

Authors:

Dinesh BharadiaAuthors Info & Claims

ACM SIGCOMM '23: Proceedings of the ACM SIGCOMM 2023 Conference

Pages 1162 - 1164

https://doi.org/10.1145/3603269.3610867

Published: 01 September 2023 Publication History

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Abstract

NextG cellular networks must support diverse applications, such as interactive media streaming or robot control that have strict requirements on throughput, latency and reliability. These requirements must be met via optimizing wireless resources by utilizing application layer information, such as media streaming stall counts or robot pose estimates, along with network information, such as channel qualities and backlogs.

References

[1]

L. Bonati, S. D'Oro, S. Basagni, and T. Melodia, "SCOPE: an open and softwarized prototyping platform for NextG systems," in MobiSys, 2021.

Google Scholar

[2]

S. D'Oro, M. Polese, L. Bonati, H. Cheng, and T. Melodia, "dApps: Distributed applications for real-time inference and control in O-RAN," IEEE Communications Magazine, vol. 60, no. 11, pp. 52--58, 2022.

Google Scholar

[3]

R. Schmidt, M. Irazabal, and N. Nikaein, "FlexRIC: An SDK for next-generation SD-RANs," in CoNEXT '21, Virtual Event, 2021.

Google Scholar

[4]

"srsRAN, Inc." https://www.srslte.com/, 2023.

Google Scholar

[5]

J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov, "Proximal policy optimization algorithms," arXiv:1707.06347, 2017.

Google Scholar

Cited By

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Cannatà RSun HDumitriu DHassanieh H(2024)Towards Seamless 5G Open-RAN Integration with WebAssemblyProceedings of the 23rd ACM Workshop on Hot Topics in Networks10.1145/3696348.3696864(121-131)Online publication date: 18-Nov-2024
https://dl.acm.org/doi/10.1145/3696348.3696864
Bura ABobbili SRameshkumar SRengarajan DKalathil DShakkottai SPapavassiliou SSchmid S(2024)Structured Reinforcement Learning for Media Streaming at the Wireless EdgeProceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3641512.3686386(101-110)Online publication date: 14-Oct-2024
https://dl.acm.org/doi/10.1145/3641512.3686386
Aslan FIosifidis GAyala-Romero JGarcia-Saavedra ACosta-Perez X(2024)Fair Resource Allocation in Virtualized O-RAN PlatformsProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/36390438:1(1-34)Online publication date: 21-Feb-2024
https://dl.acm.org/doi/10.1145/3639043
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Index Terms

Demo: EdgeRIC: Delivering Realtime RAN Intelligence
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Reinforcement learning
2. Networks
  1. Network algorithms
    1. Control path algorithms
      1. Network resources allocation

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Information & Contributors

Information

Published In

ACM SIGCOMM '23: Proceedings of the ACM SIGCOMM 2023 Conference

September 2023

1217 pages

ISBN:9798400702365

DOI:10.1145/3603269

Chairs:
Henning Schulzrinne,
Vishal Misra,
Program Chairs:
Eddie Kohler,
David Maltz

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2023

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Author Tags

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Demonstration

Funding Sources

Conference

ACM SIGCOMM '23

Sponsor:

SIGCOMM

ACM SIGCOMM '23: ACM SIGCOMM 2023 Conference

September 10, 2023

NY, New York, USA

Acceptance Rates

Overall Acceptance Rate 462 of 3,389 submissions, 14%

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Cited By

View all

Cannatà RSun HDumitriu DHassanieh H(2024)Towards Seamless 5G Open-RAN Integration with WebAssemblyProceedings of the 23rd ACM Workshop on Hot Topics in Networks10.1145/3696348.3696864(121-131)Online publication date: 18-Nov-2024
https://dl.acm.org/doi/10.1145/3696348.3696864
Bura ABobbili SRameshkumar SRengarajan DKalathil DShakkottai SPapavassiliou SSchmid S(2024)Structured Reinforcement Learning for Media Streaming at the Wireless EdgeProceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3641512.3686386(101-110)Online publication date: 14-Oct-2024
https://dl.acm.org/doi/10.1145/3641512.3686386
Aslan FIosifidis GAyala-Romero JGarcia-Saavedra ACosta-Perez X(2024)Fair Resource Allocation in Virtualized O-RAN PlatformsProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/36390438:1(1-34)Online publication date: 21-Feb-2024
https://dl.acm.org/doi/10.1145/3639043
Li ZWang QWang YChen TGanesan DLane NShi W(2024)The Architecture of AI and Communication Integration towards 6G: An O-RAN EvolutionProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3701550(2329-2334)Online publication date: 4-Dec-2024
https://dl.acm.org/doi/10.1145/3636534.3701550
An QDoost-Mohammady RYang RSridhar KGanesan DLane NShi W(2024)DRAGON: A DRL-based MIMO Layer and MCS Adapter in Open RAN 5G NetworksProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3701549(2323-2328)Online publication date: 4-Dec-2024
https://dl.acm.org/doi/10.1145/3636534.3701549
Jiao LShao YSun LLiu FYang SMa WLi LLiu XHou BZhang XShang RLi YWang STang XGuo Y(2024)Advanced Deep Learning Models for 6G: Overview, Opportunities, and ChallengesIEEE Access10.1109/ACCESS.2024.341890012(133245-133314)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3418900
Musa AHussaini AQian CGuo YYu W(2023)Open Radio Access Networks for Smart IoT Systems: State of Art and Future DirectionsFuture Internet10.3390/fi1512038015:12(380)Online publication date: 27-Nov-2023
https://doi.org/10.3390/fi15120380

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