TENORAN: Automating Fine-grained Energy Efficiency Profiling in Open RAN Systems

TL;DR

TENORAN is an automated framework that enables fine-grained energy efficiency profiling of Open RAN systems, facilitating resource optimization and energy savings through precise measurements and analysis.

Contribution

It introduces TENORAN, a novel automated measurement framework for detailed energy profiling in heterogeneous Open RAN deployments, supporting end-to-end analysis.

Findings

Energy profiling of RAN components reveals efficiency differences between OpenAirInterface and srsRAN.

The framework enables measurement of energy consumption during controlled workloads.

Insights into core network power consumption trends were obtained.

Abstract

The transition to disaggregated and interoperable Open Radio Access Network (RAN) architectures and the introduction of RAN Intelligent Controllers (RICs) in O-RAN creates new resource optimization opportunities and fine-grained tuning and configuration of network components to save energy while fulfilling service demand. However, unlocking this potential requires fine-grained and accurate energy measurements across heterogeneous deployments. Three factors make this particularly challenging [...]. To address these challenges, we design the TENORAN framework, an automated measurement scaffold for fine-grained energy efficiency profiling of O-RAN deployments, and prototype it on a heterogeneous OpenShift cluster. TENORAN instruments an end-to-end deployment based on high-level specifications (e.g., gNB software stack and split options, traffic profiles), and collects synchronized performance metrics and power measurements for individual RAN components while the network is under controlled workloads including over-the-air traffic. Our experimental results demonstrate energy profiling of end-to-end experiments with xApps in the loop, energy efficiency differences between two RAN stacks, OpenAirInterface and srsRAN, in uplink and downlink, and core network power consumption trends.