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Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond
by
Contreras, Luis M.
, Brito, Jorge Andrés
, Moreno, José Ignacio
in
5G and beyond
/ Automation
/ Communications traffic
/ Comparative analysis
/ Cost control
/ Edge computing
/ Energy consumption
/ Energy efficiency
/ energy proportionality
/ Flexibility
/ Infrastructure
/ Management
/ Network interface cards
/ Network management software
/ Open standards
/ programmable data planes
/ Protocol
/ SDN
/ Software
/ Traffic control
/ traffic management
2025
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Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond
by
Contreras, Luis M.
, Brito, Jorge Andrés
, Moreno, José Ignacio
in
5G and beyond
/ Automation
/ Communications traffic
/ Comparative analysis
/ Cost control
/ Edge computing
/ Energy consumption
/ Energy efficiency
/ energy proportionality
/ Flexibility
/ Infrastructure
/ Management
/ Network interface cards
/ Network management software
/ Open standards
/ programmable data planes
/ Protocol
/ SDN
/ Software
/ Traffic control
/ traffic management
2025
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Do you wish to request the book?
Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond
by
Contreras, Luis M.
, Brito, Jorge Andrés
, Moreno, José Ignacio
in
5G and beyond
/ Automation
/ Communications traffic
/ Comparative analysis
/ Cost control
/ Edge computing
/ Energy consumption
/ Energy efficiency
/ energy proportionality
/ Flexibility
/ Infrastructure
/ Management
/ Network interface cards
/ Network management software
/ Open standards
/ programmable data planes
/ Protocol
/ SDN
/ Software
/ Traffic control
/ traffic management
2025
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Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond
Journal Article
Energy-Aware Edge Infrastructure Traffic Management Using Programmable Data Planes in 5G and Beyond
2025
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Overview
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.
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