Deep learning-driven forecasting of cloud resource utilisation using PSO-enhanced LSTM for cost-effective scaling

Key Points

• The aim is to develop a deep learning model for accurately forecasting cloud resource utilization.
• Utilized a PSO-enhanced LSTM algorithm for forecasting
• Evaluated resource utilization data
• Implemented cost-effective scaling strategies
• Achieved significant accuracy improvements in resource utilization forecasts
• Demonstrated effective cost management in cloud scaling
• Indicated potential reductions in operational expenses through improved forecasting