Cloud service recommender system using clustering

The prevalence of cloud computing has resulted in an increased number of services developed for the Web. Selecting an appropriate cloud service from amongst a lot of commonly featured available services has become very difficult particularly for non-IT users i.e. it is cumbersome for users to select a cloud service that is best suited to their requirements. Quality of service (QOS) is considered as one of the main criterion in the selection process. This paper focuses on cloud service selection method allowing users to specify their perception of quality criteria. Our approach is based on the data mining technique clustering which is an unsupervised learning technique. Developed algorithm classifies the cloud services into different number of groups based on selected quality attributes and ranks them accordingly. The research aims to assist every type of users for choosing a cloud service without engaging into any financial contract. In order to validate our approach of best service selection, we test our system with cloud vendors like Google, Microsoft, and Amazon.

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