¹School of Finance & Public Administration, Anhui University of Finance and Economics, China
²Department of Statistics and Information Science & Applied Statistics, Fu Jen Catholic University, Taipei Hsien
³Department of Statistics, School of Economics, Xiamen University, Fujian Province, 361005

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Abstract—Owing to the less limitation of Cloud Computing, different fields (such as telecommunications, tour and medical industry etc.) can combine their industrial specialty and professional skills with Internet to construct many small clouds in Cloud Computing. In addition, like many gear wheels in the machines, many small clouds support a large cloud that is composed of different services to provide users with general-purpose applications in Cloud Computing. By the concept of Parallel Computing, we build a small cloud for statistical forecasting service (FaaS, Forecasting as a Service) with integrating Cloud Computing and data mining methods based on R, PHP and MySQL. The greatest advantage on R is that it is open and free. Moreover, R code can combine with PHP code to be a web page. Furthermore, it can solve the installation and extension problems by cloud computing that makes enterprises not that “heavy”.

Index Terms—Cloud Computing, Parallel Computing, Data Mining, FaaS, R, SQL.

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Cite: Tong Yang, Ben-Chang Shia, Jinrui Wei, and Kuangnan Fang"Mass Data Analysis and Forecasting Based on Cloud Computing," Journal of Software vol. 7, no. 10, pp. 2189-2195, 2012.