@inproceedings{10.1145/3472735.3474458,
author = {Boutaba, Raouf and Shahriar, Nashid and Salahuddin, Mohammad A. and Chowdhury, Shihabur R. and Saha, Niloy and James, Alexander},
title = {AI-Driven Closed-Loop Automation in 5G and beyond Mobile Networks},
year = {2021},
isbn = {9781450386340},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3472735.3474458},
doi = {10.1145/3472735.3474458},
abstract = {The 5th Generation (5G) mobile networks support a wide range of services that impose
diverse and stringent QoS requirements. This will be further exacerbated with the
evolution towards 6th Generation mobile networks. Inevitably, 5G and beyond mobile
networks must provide stricter, differentiated QoS guarantees to meet the increasing
demands of future applications, which cannot be satisfied with traditional human-in-the-loop
service orchestration and network management approaches. In this paper, we lay out
our vision for closed-loop service orchestration and network management of 5G and
beyond mobile networks. We extend the MAPE (i.e., monitor, analyze, plan, and execute)
control loop to facilitate closed-loop automation, and discuss the quintessential
role of Artificial Intelligence/Machine Learning in its realization. We also instigate
open research challenges for closed-loop automation of 5G and beyond mobile networks.},
booktitle = {Proceedings of the 4th FlexNets Workshop on Flexible Networks Artificial Intelligence Supported Network Flexibility and Agility},
pages = {1–6},
numpages = {6},
keywords = {machine learning, closed-loop orchestration and management, artificial intelligence, 5G},
location = {Virtual Event, USA},
series = {FlexNets '21}
}