Energy-Aware CPU Orchestration in O-RAN: A dApp-Driven Lightweight Approach

TL;DR

This paper presents a lightweight, programmable dApp for O-RAN that dynamically manages CPU resources to improve energy efficiency and performance without requiring hardware modifications.

Contribution

It introduces a novel, no-proprietary, no-kernel-modification dApp for CPU orchestration in O-RAN, enhancing energy efficiency and real-time performance.

Findings

Achieves power savings in real deployments.

Maintains real-time processing performance.

Requires minimal overhead.

Abstract

The transition toward softwarized Radio Access Networks (RANs), driven by the Open RAN (O-RAN) paradigm, enables flexible, vendor-neutral deployments through disaggregation and virtualization of base station functions. However, this shift introduces new challenges in managing CPU resources efficiently under strict real-time constraints. In particular, the interplay between latency-sensitive RAN workloads and general-purpose Operating System (OS) schedulers often leads to sub-optimal performance and unnecessary energy consumption. This work proposes a lightweight, programmable distributed application (dApp) deployed at the Distributed Unit (DU) level to dynamically orchestrate CPU usage. The dApp operates in closed loop with the OS, leveraging thread-level telemetry like context switches, Instructions Per Cycle (IPC), and cache metrics, to adapt CPU thread affinity, core isolation, and frequency scaling in real time. Unlike existing solutions, it requires no access to proprietary RAN software, hardware-specific features, or kernel modifications. Fully compliant with the O-RAN architecture and agnostic to the underlying RAN stack, the proposed solution introduces negligible overhead while improving energy efficiency and CPU utilization. Experimental results using a commercial-grade srsRAN deployment demonstrate consistent power savings without compromising real-time processing performance, highlighting the potential of low-latency dApps for fine-grained resource control in next-generation networks