Machine learning methods for reliable resource provisioning in edge-cloud computing: A survey

TL Duc, RG Leiva, P Casari, PO Östberg - ACM Computing Surveys …, 2019 - dl.acm.org
Large-scale software systems are currently designed as distributed entities and deployed in
cloud data centers. To overcome the limitations inherent to this type of deployment …

Survey on prediction models of applications for resources provisioning in cloud

M Amiri, L Mohammad-Khanli - Journal of Network and Computer …, 2017 - Elsevier
According to the dynamic nature of cloud and the rapid growth of the resources demand in it,
the resource provisioning is one of the challenging problems in the cloud environment. The …

Machine learning based workload prediction in cloud computing

J Gao, H Wang, H Shen - 2020 29th international conference …, 2020 - ieeexplore.ieee.org
As a widely used IT service, more and more companies shift their services to cloud
datacenters. It is important for cloud service providers (CSPs) to provide cloud service …

Resource central: Understanding and predicting workloads for improved resource management in large cloud platforms

E Cortez, A Bonde, A Muzio, M Russinovich… - Proceedings of the 26th …, 2017 - dl.acm.org
Cloud research to date has lacked data on the characteristics of the production virtual
machine (VM) workloads of large cloud providers. A thorough understanding of these …

Service placement and request scheduling for data-intensive applications in edge clouds

V Farhadi, F Mehmeti, T He, TF La Porta… - IEEE/ACM …, 2021 - ieeexplore.ieee.org
Mobile edge computing provides the opportunity for wireless users to exploit the power of
cloud computing without a large communication delay. To serve data-intensive applications …

A hierarchical framework of cloud resource allocation and power management using deep reinforcement learning

N Liu, Z Li, J Xu, Z Xu, S Lin, Q Qiu… - 2017 IEEE 37th …, 2017 - ieeexplore.ieee.org
Automatic decision-making approaches, such as reinforcement learning (RL), have been
applied to (partially) solve the resource allocation problem adaptively in the cloud computing …

Workload prediction in cloud using artificial neural network and adaptive differential evolution

J Kumar, AK Singh - Future Generation Computer Systems, 2018 - Elsevier
Cloud computing has drastically transformed the means of computing in recent years. In
spite of numerous benefits, it suffers from some challenges too. Major challenges of cloud …

Integrated deep learning method for workload and resource prediction in cloud systems

J Bi, S Li, H Yuan, MC Zhou - Neurocomputing, 2021 - Elsevier
Cloud computing providers face several challenges in precisely forecasting large-scale
workload and resource time series. Such prediction can help them to achieve intelligent …

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 …

Toward cloud computing QoS architecture: Analysis of cloud systems and cloud services

MH Ghahramani, MC Zhou… - IEEE/CAA Journal of …, 2017 - ieeexplore.ieee.org
Cloud can be defined as a new computing paradigm that provides scalable, on-demand,
and virtualized resources for users. In this style of computing, users can access a shared …