- Cloud Computing Virtual Machine Workload Prediction Method ...🔍
- Deep Reinforcement Learning for Workload Prediction in Federated ...🔍
- Workload Prediction Using VMD and TCN in Cloud Computing🔍
- Workload forecasting and energy state estimation in cloud data ...🔍
- Integrated deep learning method for workload and resource ...🔍
- AN EFFICIENT MACHINE LEARNING APPROACH FOR VIRTUAL ...🔍
- Taylor CFRO|Based Deep Learning Model for Service|Level ...🔍
- Deep Learning|Driven Workload Prediction and Optimization...🔍
A deep learning approach for VM workload prediction in the cloud
Cloud Computing Virtual Machine Workload Prediction Method ...
The paper proposes a method for predicting the workload of virtual machines in the cloud infrastructure.
Deep Reinforcement Learning for Workload Prediction in Federated ...
By incorporating key metrics such as energy consumption, SLA violations, VM migrations, and migration durations, our solution offers a comprehensive approach.
Workload Prediction Using VMD and TCN in Cloud Computing
Guo, “A deep learning approach for VM workload prediction in the cloud,”. Proc. 17th IEEE/ACIS. International Conference on Software Engineering, Artificial.
Workload forecasting and energy state estimation in cloud data ...
We chose one month of fastStorage trace data for the proposed method's learning, which includes the performance of 1250 VMs running in a distributed data centre ...
Integrated deep learning method for workload and resource ... - OUCI
Publications that cite this publication · Workload Time Series Cumulative Prediction Mechanism for Cloud Resources Using Neural Machine Translation Technique.
AN EFFICIENT MACHINE LEARNING APPROACH FOR VIRTUAL ...
“A deep learning approach for VM workload prediction in the cloud.” 17th. IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence ...
Taylor CFRO-Based Deep Learning Model for Service-Level ...
... Deep Belief Network (DBN) approach is designed for workload prediction and. ... VM Migration and Workload Prediction-Enabled Power Model in Cloud Computing.
VTGAN: hybrid generative adversarial networks for cloud workload ...
Deep learning (DL) methods have stirred remarkable attention during the artificial intelligence revolution in recent years. Deep-learning-based ...
Deep Learning-Driven Workload Prediction and Optimization...
Deep Learning-Driven Workload Prediction and Optimization for Load Balancing in Cloud Computing Environment · Published Online: Sep 19, 2024.
A Dynamic, Novel Unified Methodology for predicting Cloud ...
[...]the proposed algorithm which is the architecture of deep learning is used to forecast virtual machine workloads in the cloud services. LITERATURE SURVEY ...
A Self-Optimized Generic Workload Prediction Framework for Cloud ...
load predictors for various dynamic workloads. LoadDynamics employs the machine-learning (ML) model, Long-short Term. Memory (LSTM) [17], to make predictions.
a self-adaptive deep learning-based model to predict cloud workload
According to these comparisons with the state-of-the- art deep learning methods, our proposed model encompasses a better prediction efficiency and enhances ...
MAG-D: A multivariate attention network based approach for cloud ...
[45] proposed a multiscale ensemble model combining LSTM and GAN based deep learning architecture cloud workload forecasting, which has produced ...
Workload forecasting and energy state estimation in cloud data ...
As a consequence, using an ensemble learning method that involves several machine learning algo- rithms to predict both provisioned and used non-linear ...
workload forecasting and resource management models based on ...
Thereafter, a thorough survey of existing state-of-the-art contributions empowering machine learning based approaches in the field of cloud ...
An Efficient Deep Learning Model to Predict Cloud Workload for ...
... deep learning model is applied to the workload prediction of virtual machines on cloud. Experiments are conducted on the datasets collected from PlanetLab ...
Generating Complex, Realistic Cloud Workloads using Recurrent ...
A deep learning approach for VM workload prediction in the cloud. In 2016 17th IEEE/ACIS International. Conference on Software Engineering, Artificial ...
Performance Analysis of Machine Learning Centered Workload ... - CS
The review procedure includes the gathering of major cloud workload prediction papers wherein the proposed approaches are driven from machine learning ...
A novel workload forecasting model for cloud computing using ALAA ...
... A deep learning approach for VM workload prediction in the cloud. In: 2016 ... neural network model to predict the CPU workload of cloud virtual machine.
SGA Model for Prediction in Cloud Environment
The creation of an appropriate statistical method has begun. In this study, a simulation approach and a genetic algorithm were used to forecast workloads. In ...