Abstract

Cloud computing provides broad viewpoints for open environment mathematical formalism which has several key characteristics, such as reliability, versatility and network-independence. Cloud platforms are distributed and transmitted to third parties and consumers in an agnostic network architecture. Software and tools are distributed and delivered. Service providers may confront various categories of clients, but cannot completely forecast their behaviour, while service consumers have little ability to dictate the transfer of user data and services frequently delivered in a specially configured hosting place. Consumers also cannot have faith in these opportunities in the cloud infrastructure. In this paper, the software is readily available and promises higher accuracy and consistent performance. For clustering different distributed data, we have used the K-means clustering technique that groups the data of the whole individual and improves efficiency. We have installed all cluster results and graphically map different data attributes