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Power Efficiency of a Hybrid 5G gNB Data Plane Combining SmartNICs and Commodity Servers
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed Intelligent Systems and Communication (DISCO))
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). Deggendorf Institute of Technology, Deggendorf, DE. (Distributed Intelligent Systems and Communication (DISCO))ORCID iD: 0000-0002-9446-8143
Karlstad University, Faculty of Economic Sciences, Communication and IT (discontinued), Department of Computer Science. Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed Intelligent Systems and Communication (DISCO))ORCID iD: 0000-0003-4147-9487
Eotvos Lorand Tudomanyegyetem Informatikai Kar: Budapest, HU.ORCID iD: /0000-0002-8875-5330
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2025 (English)In: The 4th GI/ITG KuVS Fachgespräch "Network Softwarization" (KuVS FGNetSoft), April 3, On-line., 2025Conference paper, Published paper (Refereed)
Abstract [en]

Power efficiency is crucial in softwarized 5G gNBs due to rising energy costs and CO_2 emissions from the networking infrastructure. SmartNICs have the potential to accelerate packet processing tasks. However, their limited resources and functionalities make handling complex tasks like retransmissions challenging. Offloading operations to server-class processors can improve scalability but also increase power consumption, warranting careful management. This study examines the performance and power consumption of splitting the processing of the 5G gNB between SmartNICs and DPDK-enabled servers. We implement an adaptive CPU power conserving strategy in the DPDK data plane that dynamically adjusts CPU power states using P-states and C-states based on traffic load. Our evaluation shows that when using five SmartNICs, we can achieve 95 MPPS, demonstrating that offloading can boost throughput by up to 40% for gNB header processing. Our adaptive power management limits CPU power consumption growth to a maximum of 11%, compared to 52% without such management, balancing performance and power efficiency effectively.

Place, publisher, year, edition, pages
2025.
Keywords [en]
5G gNB, P4, Data Plane, SmartNIC
National Category
Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-103632OAI: oai:DiVA.org:kau-103632DiVA, id: diva2:1947040
Conference
The 4th GI/ITG KuVS Fachgespräch "Network Softwarization" (KuVS FGNetSoft)
Projects
Datadrivna latenskänsliga mobila tjänster för ett digitaliserat samhälle (DRIVE)
Funder
Knowledge FoundationAvailable from: 2025-03-24 Created: 2025-03-24 Last updated: 2025-03-24

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Kassler, AndreasGrinnemo, Karl-JohanLaki, SándorPongracz, Gergely
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