Multivariate Resource Usage Prediction With Frequency-Enhanced and Attention-Assisted Transformer in Cloud Computing Systems

Keyphrases

• Forecasting Techniques 100%
• Prediction Method 100%
• Cloud Computing System 100%
• Cloud Environment 100%
• Transformer 100%
• Transformer Model 100%
• Savitzky-Golay Filter 100%
• Resource Prediction 100%
• Channel Attention Mechanism 100%
• Enhanced Channel Attention 100%
• Quality of Service 50%
• Noise Reduction 50%
• Prediction Accuracy 50%
• Resource Utilization 50%
• Deep Learning Model 50%
• Recurrent Neural Network 50%
• Cloud Data Center 50%
• Efficient Prediction 50%
• Domain Patterns 50%
• Vanilla 50%
• Informer 50%
• High Volatility 50%
• Vital Data 50%
• Particle Swarm Optimizer 50%
• Training Stages 50%
• Google Cluster Trace 50%
• Long Short-term Memory 50%
• Genetic Simulated Annealing 50%
• Regression Algorithm 50%
• Hyperparameters 50%
• Nonlinear Features 50%
• Provider Services 50%
• Resource Wastage 50%
• Hybrid Transformer 50%
• Smooth Sequences 50%
• Multi-dimensional Resources 50%
• Volatility Characteristics 50%
• Realistic Dataset 50%
• Frequency Domain Features 50%
• High-precision Prediction 50%
• Metaheuristic Optimization Algorithms 50%
• Gradient Explosion 50%
• Resource Insufficiency 50%
• Gradient Vanishing 50%
• Memory Transformer 50%
• Alibaba Cluster Trace 50%

Computer Science

• Frequency Domain 100%
• Attention (Machine Learning) 100%
• Cloud Computing System 100%
• Cloud Environment 100%
• Prediction Accuracy 100%
• Forecasting Method 100%
• Data Center 50%
• Experimental Result 50%
• Recurrent Neural Network 50%
• Deep Learning Model 50%
• Simulated Annealing 50%
• particle swarm optimizer 50%
• Long Short-Term Memory Network 50%
• Metaheuristic Optimization Algorithm 50%
• Leaning Parameter 50%
• Transformer Model 50%