Design and Implementation of Cloud Computing Based Mixed Big Data Mining


  • Dr. B. V. S. Varma, Dr. A. Ramamurthy


ABSTRACT: With the application and popularization of Internet, the data of network resources are becoming more and more massive and diversified. The amount of digital data is increasing beyond any previous estimation and data stores and sources are more and more pervasive and distributed. So much data will undoubtedly bring people a vast amount of information, but the difficulty of finding useful knowledge for the enterprise or individual from the vast amount of data has increased. This paper elaborates the design and implementation of Cloud Computing based mixed Big Data Mining. Cloud computing platform can perform dynamic resource scheduling and allocation, with the characteristics of highly virtualization and high availability, which meets the needs of efficient data mining. Taking the multifunctional Hadoop big data mining platform as an example, this article analyses the internal workflow of big data mining. The performance of described model is evaluated through the execution of workflow-based data analysis applications on a pool of virtual servers hosted by a Microsoft Cloud data center. The experimental results demonstrated the effectiveness of the framework.