May 27, 2023 · Our study showed that the encoder-decoder GRU and LSTM models were able to achieve high short-term prediction outcomes. This shows a promising ...
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Nov 11, 2021 · This paper proposes an autonomic and intelligent workload forecasting method for cloud resource provisioning based on the concept of autonomic computing and a ...
In this paper, we proposed to use multivariate long short term memory (LSTM) models for prediction of resource usage in cloud workloads.
Our study utilized several regression models and deep learning models including GRU, LSTM in univariate and multivariate settings to explore and extract highly ...
(Borkowski et al., 2016) introduces Cloud resource provisioning through the use of machine learning- based models to predict resource utilisation at the task.
Jan 1, 2023 · Abstract. Modern cluster management systems have effectively evolved to deal with the increasing and diverse cloud computing demands.
This paper proposes a multivariate deep learning prediction model to predict future resource workload for cloud computing environment. The prediction model uses ...
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In the next stage, it predicts the future utilization of resources by using neural network regression model based on the classification results. The ...
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Jan 16, 2024 · This research presents a hybrid model using deep learning with Particle Swarm Intelligence and Genetic Algorithm (DPSO-GA) for dynamic workload provisioning in ...
Feb 18, 2022 · This research focuses on multi-resource utilization prediction using Functional Link Neural Network (FLNN) with hybrid Genetic Algorithm (GA) and Particle ...