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

面向 5G 及未来网络的节能型边缘基础设施流量管理:基于可编程数据平面

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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.

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