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Article

Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond

by
Jorge Andrés Brito
1,*,
José Ignacio Moreno
1 and
Luis M. Contreras
2
1
Departamento de Ingeniería de Sistemas Telemáticos, ETSI de Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, Spain
2
Telefónica Innovación Digital, 28010 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(8), 2375; https://doi.org/10.3390/s25082375
Submission received: 20 February 2025 / Revised: 6 April 2025 / Accepted: 8 April 2025 / Published: 9 April 2025
(This article belongs to the Special Issue Energy-Efficient Communication Networks and Systems: 2nd Edition)

Abstract

Next-generation networks, particularly 5G and beyond, face rising energy demands that pose both economic and environmental challenges. In this work, we present a traffic management scheme leveraging programmable data planes and an SDN controller to achieve energy proportionality, matching network resource usage to fluctuating traffic loads. This approach integrates flow monitoring on programmable switches with a dynamic power manager in the controller, which selectively powers off inactive switches. We evaluate this scheme in an emulated edge environment across multiple urban traffic profiles. Our results show that disabling switches not handling traffic can significantly reduce energy consumption, even under relatively subtle load variations, while maintaining normal network operations and minimizing overhead on the control plane. We further include a projected savings analysis illustrating the potential benefits if the solution is deployed on hardware devices such as Tofino-based switches. Overall, these findings highlight how data plane-centric, energy-aware traffic management can make 5G-and-beyond edge infrastructures both sustainable and adaptable for future networking needs.
Keywords: programmable data planes; SDN; energy proportionality; energy efficiency; traffic management; 5G and beyond; edge computing; P4; green computing programmable data planes; SDN; energy proportionality; energy efficiency; traffic management; 5G and beyond; edge computing; P4; green computing

Share and Cite

MDPI and ACS Style

Brito, J.A.; Moreno, J.I.; Contreras, L.M. Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond. Sensors 2025, 25, 2375. https://doi.org/10.3390/s25082375

AMA Style

Brito JA, Moreno JI, Contreras LM. Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond. Sensors. 2025; 25(8):2375. https://doi.org/10.3390/s25082375

Chicago/Turabian Style

Brito, Jorge Andrés, José Ignacio Moreno, and Luis M. Contreras. 2025. "Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond" Sensors 25, no. 8: 2375. https://doi.org/10.3390/s25082375

APA Style

Brito, J. A., Moreno, J. I., & Contreras, L. M. (2025). Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond. Sensors, 25(8), 2375. https://doi.org/10.3390/s25082375

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