Effective combination and application path of computer big data analysis and cloud computing network technology

[1] Li, X., He, J., Zhao, B., Fang, J., Zhang, Y., & Liang, H. (2016). A method for trust quantification in cloud computing environments. International Journal of Distributed Sensor Networks, 12(2), 5052614. Search in Google Scholar

[2] Manikyam, N. R. H., & Kumar, S. M. (2017). Methods and techniques to deal with big data analytics and challenges in cloud computing environment. International Journal of Civil Engineering and Technology, 8(4), 669-678. Search in Google Scholar

[3] Gai, K., Qiu, M., Tao, L., & Zhu, Y. (2016). Intrusion detection techniques for mobile cloud computing in heterogeneous 5g. Security & Communication Networks, 3049-3058. Search in Google Scholar

[4] Zhou, K., & Yang, S. (2016). Understanding household energy consumption behavior: the contribution of energy big data analytics. Renewable & Sustainable Energy Reviews, 56, 810-819. Search in Google Scholar

[5] Côrte-Real, Nadine, Oliveira, T., & Ruivo, P. (2017). Assessing business value of big data analytics in european firms. Journal of Business Research, 70. Search in Google Scholar

[6] Chrimes, D., Moa, B., Kuo, A., & Kushniruk, A. (2017). Operational efficiencies and simulated performance of big data analytics platform over billions of patient records of a hospital system. Advances in Science Technology and Engineering Systems Journal, 2(1), 23-41. Search in Google Scholar

[7] Jayakrishnan, M., Mohamad, A. K. B., & Mohd-Yusof, M. (2018). The holistic view of business intelligence (bi) and big data analytics (bda) towards designing strategic performance management framework: a case study. Journal of Theoretical and Applied Information Technology, 96(7). Search in Google Scholar

[8] Adrian, C., Abdullah, R., Atan, R., & Jusoh, Y. Y. (2018). Conceptual model development of big data analytics implementation assessment effect on decision-making. International Journal of Interactive Multimedia and Artificial Intelligence, 5(1), 101-106. Search in Google Scholar

[9] Egliston, B. (2016). Big playerbase, big data: on data analytics methodologies and their applicability to studying multiplayer games and culture. First Monday, 21(7). Search in Google Scholar

[10] Choi, C. Y., & Park, D. W. (2016). The analysis of the apt prelude by big data analytics. Journal of the Korea Institute of Information & Communication Engineering, 20(6), 1129-1135. Search in Google Scholar

[11] Mehdipour, F., Noori, H., & Javadi, B. (2016). Energy-efficient big data analytics in datacenters - sciencedirect. Advances in Computers, 100, 59-101. Search in Google Scholar

[12] Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., & Merle, P. (2017). Elasticity in cloud computing: state of the art and research challenges. IEEE Transactions on Services Computing, PP(99), 1-1. Search in Google Scholar

[13] Myung, R., Yu, H., & Lee, D. (2017). Optimizing parallelism of big data analytics at distributed computing system. International Journal on Advanced Science Engineering and Information Technology, 7(5), 1716. Search in Google Scholar

[14] Shah, M., Shah, A. S., & Ijaz, I. (2016). Implementation of user authentication as a service for cloud network. International Journal of Grid and Distributed Computing, 9(10), 197-210. Search in Google Scholar

[15] Chang, V., & Ramachandran, M. (2016). Towards achieving data security with the cloud computing adoption framework. IEEE Transactions on Services Computing, 138-151. Search in Google Scholar

[16] Nagaraju, S., & Parthiban, L. (2016). Secauthn: provably secure multi-factor authentication for the cloud computing systems. Indian Journal of Science & Technology, 9(9). Search in Google Scholar

[17] Zhu, W., & Lee, C. (2016). A security protection framework for cloud computing. Journal of Information Processing Systems, 12(3), 538-547. Search in Google Scholar

[18] Rezaei, H., Karimi, B., & Hosseini, S. J. (2016). Effect of cloud computing systems in terms of service quality of knowledge management systems. Lecture Notes on Software Engineering, 4(1), 73-76. Search in Google Scholar

[19] Dursun, A., & Caber, M. (2016). Using data mining techniques for profiling profitable hotel customers: an application of rfm analysis. Tourism Management Perspectives, 18, 153-160. Search in Google Scholar

[20] Sivakumar, S., Venkataraman, S., & Selvaraj, R. (2016). Predictive modeling of student dropout indicators in educational data mining using improved decision tree. Indian Journal of Science & Technology, 9(4). Search in Google Scholar