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AI-empowered fog/edge resource management for IoT applications: A comprehensive review, research challenges, and future perspectives
The proliferation of ubiquitous Internet of Things (IoT) sensors and smart devices in several
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …
domains embracing healthcare, Industry 4.0, transportation and agriculture are giving rise to …
Machine learning (ML)-centric resource management in cloud computing: A review and future directions
Cloud computing has rapidly emerged as a model for delivering Internet-based utility
computing services. Infrastructure as a Service (IaaS) is one of the most important and …
computing services. Infrastructure as a Service (IaaS) is one of the most important and …
Machine learning based workload prediction in cloud computing
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 …
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
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 …
machine (VM) workloads of large cloud providers. A thorough understanding of these …
[HTML][HTML] Prediction of home energy consumption based on gradient boosting regression tree
Energy consumption prediction of buildings has drawn attention in the related literature
since it is very complex and affected by various factors. Hence, a challenging work is …
since it is very complex and affected by various factors. Hence, a challenging work is …
Machine learning methods for reliable resource provisioning in edge-cloud computing: A survey
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 …
cloud data centers. To overcome the limitations inherent to this type of deployment …
From cloud to edge: a first look at public edge platforms
Public edge platforms have drawn increasing attention from both academia and industry. In
this study, we perform a first-of-its-kind measurement study on a leading public edge …
this study, we perform a first-of-its-kind measurement study on a leading public edge …
esDNN: deep neural network based multivariate workload prediction in cloud computing environments
Cloud computing has been regarded as a successful paradigm for IT industry by providing
benefits for both service providers and customers. In spite of the advantages, cloud …
benefits for both service providers and customers. In spite of the advantages, cloud …
[HTML][HTML] AI augmented Edge and Fog computing: Trends and challenges
In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
BHyPreC: a novel Bi-LSTM based hybrid recurrent neural network model to predict the CPU workload of cloud virtual machine
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 …
for the maximum utilization of cloud resources. It increases the computing power …