[HTML][HTML] Machine learning in beyond 5G/6G networks—State-of-the-art and future trends

VP Rekkas, S Sotiroudis, P Sarigiannidis, S Wan… - Electronics, 2021 - mdpi.com
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …

Toward a smart cloud: A review of fault-tolerance methods in cloud systems

MA Mukwevho, T Celik - IEEE Transactions on Services …, 2018 - ieeexplore.ieee.org
This paper presents a comprehensive survey of the state-of-the-art work on fault tolerance
methods proposed for cloud computing. The survey classifies fault-tolerance methods into …

Machine learning-based scaling management for kubernetes edge clusters

L Toka, G Dobreff, B Fodor… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Kubernetes, the container orchestrator for cloud-deployed applications, offers automatic
scaling for the application provider in order to meet the ever-changing intensity of …

A proactive autoscaling and energy-efficient VM allocation framework using online multi-resource neural network for cloud data center

D Saxena, AK Singh - Neurocomputing, 2021 - Elsevier
This work proposes an energy-efficient resource provisioning and allocation framework to
meet dynamic demands of the future applications. The frequent variations in a cloud user's …

AI-based resource provisioning of IoE services in 6G: A deep reinforcement learning approach

H Sami, H Otrok, J Bentahar… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Currently, researchers have motivated a vision of 6G for empowering the new generation of
the Internet of Everything (IoE) services that are not supported by 5G. In the context of 6G …

Horizontal and vertical scaling of container-based applications using reinforcement learning

F Rossi, M Nardelli, V Cardellini - 2019 IEEE 12th International …, 2019 - ieeexplore.ieee.org
Software containers are changing the way distributed applications are executed and
managed on cloud computing resources. Interestingly, containers offer the possibility of …

Applying reinforcement learning towards automating energy efficient virtual machine consolidation in cloud data centers

R Shaw, E Howley, E Barrett - Information Systems, 2022 - Elsevier
Energy awareness presents an immense challenge for cloud computing infrastructure and
the development of next generation data centers. Virtual Machine (VM) consolidation is one …

Geo-distributed efficient deployment of containers with kubernetes

F Rossi, V Cardellini, FL Presti, M Nardelli - Computer Communications, 2020 - Elsevier
Software containers are changing the way applications are designed and executed.
Moreover, in the last few years, we see the increasing adoption of container orchestration …

Architectural principles for cloud software

C Pahl, P Jamshidi, O Zimmermann - ACM Transactions on Internet …, 2018 - dl.acm.org
A cloud is a distributed Internet-based software system providing resources as tiered
services. Through service-orientation and virtualization for resource provisioning, cloud …

Reinforcement learning-based application autoscaling in the cloud: A survey

Y Garí, DA Monge, E Pacini, C Mateos… - … Applications of Artificial …, 2021 - Elsevier
Reinforcement Learning (RL) has demonstrated a great potential for automatically solving
decision-making problems in complex, uncertain environments. RL proposes a …