Fair resource allocation in virtualized O-RAN platforms

Fair resource allocation in virtualized O-RAN platforms

Aslan, F.A. (TU Delft Networked Systems)
Iosifidis, G. (TU Delft Networked Systems)
Ayala-Romero, Jose A. (NEC Laboratories Europe)
Garcia-Saavedra, Andres (NEC Laboratories Europe)
Costa-Perez, Xavier (NEC Laboratories Europe; ICREA)

2024

O-RAN systems and their deployment in virtualized general-purpose computing platforms (O-Cloud) constitute a paradigm shift expected to bring unprecedented performance gains. However, these architectures raise new implementation challenges and threaten to worsen the already-high energy consumption of mobile networks. This paper presents first a series of experiments which assess the O-Cloud's energy costs and their dependency on the servers' hardware, capacity and data traffic properties which, typically, change over time. Next, it proposes a compute policy for assigning the base station data loads to O-Cloud servers in an energy-efficient fashion; and a radio policy that determines at near-real-Time the minimum transmission block size for each user so as to avoid unnecessary energy costs. The policies balance energy savings with performance, and ensure that both of them are dispersed fairly across the servers and users, respectively. To cater for the unknown and time-varying parameters affecting the policies, we develop a novel online learning framework with fairness guarantees that apply to the entire operation horizon of the system (long-Term fairness). The policies are evaluated using trace-driven simulations and are fully implemented in an O-RAN compatible system where we measure the energy costs and throughput in realistic scenarios.

Energy Efficiency
Fairness
Mobile Networks
O-RAN
Online Learning
Regret
Resource Management

http://resolver.tudelft.nl/uuid:765c3f37-44fe-4247-9a28-50645ac03819

https://doi.org/10.1145/3639043

2476-1249

Proceedings of the ACM on Measurement and Analysis of Computing Systems, 8 (1), 34

Institutional Repository

journal article

© 2024 F.A. Aslan, G. Iosifidis, Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez