An effective deep learning architecture leveraging BIRCH clustering for resource usage prediction of heterogeneous machines in cloud data center

Keyphrases

• Resource Utilization 100%
• Cloud Data Center 100%
• Deep Learning Architectures 100%
• Long Short-term Memory 100%
• Heterogeneous Machines 100%
• Resource Prediction 100%
• Transformer 100%
• Hierarchical Clustering 100%
• Long-range Dependence 75%
• Machine Learning 50%
• Sequence Order 50%
• Informer Model 50%
• Artificial Intelligence Techniques 25%
• Cloud Computing 25%
• Modern History 25%
• Physical Machine 25%
• Best Solution 25%
• Intelligence Learning 25%
• Deep Learning Model 25%
• Google Cluster Trace 25%
• Long Short-term Memory Model 25%
• Transformer Architecture 25%
• Energy Footprint 25%
• Usage Time 25%
• Input Sequence 25%
• Hierarchy Algorithm 25%
• Economic Services 25%
• Informer 25%
• All-subsets 25%
• Short-term Forecasting 25%
• Advanced Analytics 25%
• Handling Noise 25%

Computer Science

• Data Center 100%
• Long Short-Term Memory Network 100%
• Deep Learning Method 100%
• Range Dependency 60%
• Machine Learning 40%
• Learning System 40%
• Resource Utilisation 20%
• Physical Machine 20%
• Deep Learning Model 20%
• Memory Model 20%
• Artificial Intelligence 20%
• Cloud Computing 20%

Engineering

• Resource Usage 100%
• Long Short-Term Memory 100%
• Deep Learning Method 100%
• Learning System 40%
• Artificial Intelligence Technique 20%
• Limitations 20%
• Cloud Computing 20%
• Resource Utilisation 20%
• Input Sequence 20%
• Energy Footprint 20%