Time Series Forecasting of Cloud Resource Usage

Abstract

In recent cloud computing research, the allocation of virtual resources has become a major concern. The Virtual Machine (VM) dynamic deployment technique is one of the key virtual resource management techniques. Virtual resource management predicts the resources on the virtual machine and manages accordingly. The study of the Virtual Machine resource dynamic deployment focuses on the fine-grained resource adjustment strategy. So, there is a need for predicting the usage of resources for the virtual machine to avoid delays, overprovisioning and under provisioning. Time series forecasting models are used because predictions of cloud resources are dependent on time. In this paper, different time series models and ensemble techniques have been fitted to predict resource usage for successive hours. Different time series analysis techniques were implemented to study the dataset and to choose the appropriate model. Various types of resources such as CPU usage, disk read times, disk write times and memory usage are predicted using the above models.