EdgeBOL

EdgeBOL: A Bayesian Learning Approach for the Joint Orchestration of vRANs and Mobile Edge AI

Ayala-Romero, Jose A. (NEC Laboratories Europe)
Garcia-Saavedra, Andres (NEC Laboratories Europe)
Costa-Perez, Xavier (NEC Laboratories Europe; i2CAT Foundation and ICREA)
Iosifidis, G. (TU Delft Networked Systems)

2023

Future mobile networks need to support intelligent services which collect and process data streams at the network edge, so as to offer real-time and accurate inferences to users. However, the widespread deployment of these services is hindered by the unprecedented energy cost they induce to the network, and by the difficulties in optimizing their end-to-end operation. To address these challenges, we propose a Bayesian learning framework for jointly configuring the service and the Radio Access Network (RAN), aiming to minimize the total energy consumption while respecting accuracy and latency service requirements. Using a fully-fledged prototype with a software-defined base station (vBS) and a GPU-enabled edge server, we profile a typical video analytics service and identify new performance trade-offs and optimization opportunities. Accordingly, we tailor the proposed learning framework to account for the (possibly varying) network conditions, user needs, and service metrics, and apply it to a range of experiments with real traces. Our findings suggest that this approach effectively adapts to different hardware platforms and service requirements, and outperforms state-of-the-art benchmarks based on neural networks.

Base stations
Bayes methods
Bayesian online learning
Costs
edge computing
Energy efficiency
machine learning
network virtualization
Optimization
Performance evaluation
Power demand
Servers
wireless testbeds

http://resolver.tudelft.nl/uuid:ffa6c914-c6c1-4391-8fb7-dbb4870ae353

https://doi.org/10.1109/TNET.2023.3268981

2024-01-04

1063-6692

IEEE - ACM Transactions on Networking, 31 (6), 2978 - 2993

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez, G. Iosifidis