Machine learning for service migration: a survey

N Toumi, M Bagaa, A Ksentini - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
Future communication networks are envisioned to satisfy increasingly granular and dynamic
requirements to accommodate the application and user demands. Indeed, novel immersive …

Efficient VM migrations using forecasting techniques in cloud computing: a comprehensive review

M Masdari, H Khezri - Cluster Computing, 2020 - Springer
High cost of data centers' energy consumption and its environmental effects such as CO 2
emissions have inspired numerous researches to provide more efficient VM management …

BHyPreC: a novel Bi-LSTM based hybrid recurrent neural network model to predict the CPU workload of cloud virtual machine

ME Karim, MMS Maswood, S Das, AG Alharbi - IEEE Access, 2021 - ieeexplore.ieee.org
With the advancement of cloud computing technologies, there is an ever-increasing demand
for the maximum utilization of cloud resources. It increases the computing power …

Towards accurate prediction for high-dimensional and highly-variable cloud workloads with deep learning

Z Chen, J Hu, G Min, AY Zomaya… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Resource provisioning for cloud computing necessitates the adaptive and accurate
prediction of cloud workloads. However, the existing methods cannot effectively predict the …

Predicting host CPU utilization in the cloud using evolutionary neural networks

K Mason, M Duggan, E Barrett, J Duggan… - Future Generation …, 2018 - Elsevier
Abstract The Infrastructure as a Service (IaaS) platform in cloud computing provides
resources as a service from a pool of compute, network, and storage resources. One of the …

A hybrid CNN-LSTM model for predicting server load in cloud computing

E Patel, DS Kushwaha - The Journal of Supercomputing, 2022 - Springer
Complex resource usage patterns of scaling Cloud workloads and heterogeneous
infrastructure remain a challenge for accurate modelling of server load, which is the key to …

HANSEL: Adaptive horizontal scaling of microservices using Bi-LSTM

M Yan, XM Liang, ZH Lu, J Wu, W Zhang - Applied Soft Computing, 2021 - Elsevier
With the rapid development of 5G network, business scenarios such as intelligent service
and new retail are becoming more and more popular. The demand for more flexible and …

A systematic review on effective energy utilization management strategies in cloud data centers

SS Panwar, MMS Rauthan, V Barthwal - Journal of Cloud Computing, 2022 - Springer
Data centers are becoming considerably more significant and energy-intensive due to the
exponential growth of cloud computing. Cloud computing allows people to access computer …

Adaptive prediction models for data center resources utilization estimation

W Iqbal, JL Berral, A Erradi… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Accurate estimation of data center resource utilization is a challenging task due to multi-
tenant co-hosted applications having dynamic and time-varying workloads. Accurate …

An energy efficient anti-correlated virtual machine placement algorithm using resource usage predictions

R Shaw, E Howley, E Barrett - Simulation Modelling Practice and Theory, 2019 - Elsevier
Energy related costs and environmental sustainability present a significant challenge for
cloud computing practitioners and the development of next generation data centers. Virtual …