A User-Oriented Approach toward Price Prediction for IaaS Service

With the continuous development of cloud services, the types and the number of services have increased significantly. It has become the current focus on how to find a service to meet their needs in cloud market. However in cloud market, the difficult is that how to maximize the benefit of users and make users understand the reasonable pricing of their services. So this paper proposes a method based on the ARIMA (Autoregressive Integrated Moving Average Model) model to predict the future price of the cloud service, and choose the service is used ontology collaborative filtering algorithm. Finally, we take the cloud service of infrastructure as a service (IaaS) as an example to do experiment. The experimental results show our approach can find the optimal service price accuracy. This will make it possible to provide more accuracy service to user.