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esDNN: Deep Neural Network Based Multivariate Workload Prediction in Cloud Computing Environments

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Unpaired Self-supervised Learning for Industrial Cyber-Manufacturing Spectrum Blind Deconvolution

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Enhanced Time Series Prediction with VMD: A Hybrid Deep Learning Approach

inferred← citeshttps://doi.org/10.1145/3686253openalex-snapshot

StatuScale: Status-aware and Elastic Scaling Strategy for Microservice Applications

inferred← citeshttps://doi.org/10.1145/3711129.3711277openalex-snapshot

Cloud Computing Resource Prediction Based on Adaptive Selection of Multiple Machine Learning Methods

inferred← citeshttps://doi.org/10.1145/3719003openalex-snapshot

Public Datasets for Cloud Computing: A Comprehensive Survey

inferred← citeshttps://doi.org/10.1145/3773276.3774300openalex-snapshot

Balancing Compression and Prediction: A Hybrid Autoencoder–LSTM Framework for Cloud Workloads

inferred← citeshttps://doi.org/10.1145/3784013.3784082openalex-snapshot

Discrete Temporal Prompting and Cross-Modal Alignment for Cloud Resource Forecasting

inferred← citeshttps://doi.org/10.1145/3804601.3804660openalex-snapshot

Q-SPM: A Lightweight Online Task Sequence Predictor for Adaptive Real-Time Scheduling

inferred← citeshttps://doi.org/10.1177/18758967261487873openalex-snapshot

Predicting task outcome using ensemble machine learning models

inferred← citeshttps://doi.org/10.1186/s13677-024-00698-6openalex-snapshot

When wavelet decomposition meets external attention: a lightweight cloud server load prediction model

inferred← citeshttps://doi.org/10.1186/s13677-026-00947-wopenalex-snapshot

Predicting task offloading requests and resource demands in IoT edge computing using hybrid deep learning model

inferred← citeshttps://doi.org/10.12677/csa.2026.161015openalex-snapshot

A Cloud Platform Tasks Number Prediction Method Focusing on Period-Trend-Fluctuation

inferred← citeshttps://doi.org/10.12694/scpe.v24i1.2020openalex-snapshot

MVMS: RNN based Pro-Active Resource Scaling in Cloud Environment

inferred← citeshttps://doi.org/10.14569/ijacsa.2024.01505104openalex-snapshot

Cloud Workload Prediction Based on Bayesian-Optimized Autoformer

inferred← citeshttps://doi.org/10.14569/ijacsa.2025.0160584openalex-snapshot

MICRAST: Micro-Forecasting Approach for Cloud User Consumption Pattern Based on RNN

inferred← citeshttps://doi.org/10.21203/rs.3.rs-4934203/v1openalex-snapshot

Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Domain Generalization

inferred← citeshttps://doi.org/10.2139/ssrn.5394373openalex-snapshot

Star: Spatial-Temporal Autoscaling for Cloud Applications Via Deep Reinforcement Learning

inferred← citeshttps://doi.org/10.26599/bdma.2025.9020097openalex-snapshot

CFL-LSTM: Collaborative Cloud Server Load Prediction Using Multi-Dimensional Time Series Correlation Analysis and LSTM

inferred← citeshttps://doi.org/10.26599/tst.2025.9010102openalex-snapshot

FELT: Large-Scale Cloud Workload Prediction Through Adaptive Feature-Enhanced and Similarity-Aware Transformer

inferred← citeshttps://doi.org/10.26634/jcc.12.2.22409openalex-snapshot

A hybrid approach for resource utilization prediction in cloud data center using functional link neural network and convolutional neural network

inferred← citeshttps://doi.org/10.32604/jai.2025.071133openalex-snapshot

Analysis and Prediction of Real-Time Memory and Processor Usage Using Artificial Intelligence (AI)

inferred← citeshttps://doi.org/10.3390/app152010967openalex-snapshot

PRPOS: A Periodicity-Aware Resource Prediction Framework for Online Services

inferred← citeshttps://doi.org/10.3390/electronics13183588openalex-snapshot

DuCFF: A Dual-Channel Feature-Fusion Network for Workload Prediction in a Cloud Infrastructure

inferred← citeshttps://doi.org/10.3390/electronics14071332openalex-snapshot

Towards Efficient Job Scheduling for Cumulative Data Processing in Multi-Cloud Environments

inferred← citeshttps://doi.org/10.3390/s23239436openalex-snapshot

An Autoscaling System Based on Predicting the Demand for Resources and Responding to Failure in Forecasting

inferred← citeshttps://doi.org/10.3390/sym17030383openalex-snapshot

Symmetry-Aware Multi-Dimensional Attention Spiking Neural Network with Optimization Techniques for Accurate Workload and Resource Time Series Prediction in Cloud Computing Systems

inferred← citeshttps://doi.org/10.3390/sym18081389openalex-snapshot

Cluster Resource Load Prediction Method Based on Temporal-Feature Attention and Dynamic Stacking

inferred← citeshttps://doi.org/10.48084/etasr.12374openalex-snapshot

An Attention-Based LSTM-ELECTRE Model for Intelligent and Proactive Load Balancing in Real-Time Fog Computing Environments

inferred← citeshttps://doi.org/10.55214/25768484.v8i6.3717openalex-snapshot

Optimizing quality of service forecasting in mobile networks through modified walrus optimization and multivariate approaches

inferred← citeshttps://doi.org/10.57166/riqchary.v7.n1.2025.136openalex-snapshot

Beneficios y desafíos de la integración de infraestructura en la nube en la gestión de servicios de TI: una revisión sistemática

inferred← citeshttps://doi.org/10.62411/jcta.15866openalex-snapshot

Log-Transformed Regime-Based Prediction of Cloud Job Length Using Machine Learning

inferred← citeshttps://doi.org/10.7717/peerj-cs.3964openalex-snapshot

Bridging FinOps practice and machine learning research: a systematic review of cloud cost optimization

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