Cloud-Based e-Learning Infrastructures With Load Forecasting Mechanism Based on Exponential Smoothing: A Use Case
The development of cloud technologies allows the implementation of scalable, versatile, and customized systems, constructed on-demand. This allows more efficient use of computing resources, improving the revenue of the system and enhancing the Quality of Service (QoS) received by users while minimizing the power consumption of the machines. Several research works conclude that in order to efficiently manage a cloud-based infrastructure (meaning, deploy computing resources when needed without affecting negatively to the QoS perceived by users), accurate predictions on the load of machines should be made. Thanks to this, resources can be ready to use when users need them, and shutdown when they are not needed - thus reducing the power consumption and enhancing the revenue of the system.