The Price Analysis And Prediction Of Cloud Service Based On Ontology

With the development of cloud services, the types and quantity of services the service providers provided have substantially increased. Among these similar services,users not only need to find the services which meet their needs, but also often need to consider the price of services. Users always want to be able to choose services with lower price, while cloud service providers want to be able to sell their products at higher price to get the most profit, so there will be some contradiction in price between the users and the service providers. On the other hand, cloud service providers want a reasonable allocation of service resources, and users need to find lower-priced services. Usually, both sides tend to use a predetermined way to rational consumption of services, that is, a certain period of time choose to meet the application needs, the price is relatively appropriate cloud services. However, the price of cloud services does not remain unchanged, and it will be affected by a variety of factors, such as the quality of service, the changes of service market and so on. At present, the main way for users to select cloud services is to search through the search engine to find services to meet their own needs,but the results of the search depend on the search engine's performance. The frequent fluctuations in the service price make it uncertain for users to choose right service. So a more precise service selection and price forecasting mechanism is needed to provide the user with more personalized and specialized services to help the user choose the right cloud service.Therefore, this thesis proposes a kind of ontology-based cloud service selection and price forecasting mechanism. Firstly, we establish the cloud service ontology library, and then the ontology query and reasoning technology are used to match the user's needs with the cloud service ontology knowledge, and provide users service set which meets their needs. In order to facilitate users, to maximize the profit of users and to make users understand the service price which they will buy, this thesis further proposed a price prediction method based on the ontology collaborative filtering to predict the future service price for users. Finally, based on the above methods, this thesis design and implement a system of the infrastructure services (IAAS) cloud service querying, and make it convenient to users for selecting and using cloud service.