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An Efficient Cloud Service Quality Performance Management Method Using a Time Series Framework  

Jung, Hyun Chul (Dept. of Management Engineering, Sangmyung Univ.)
Seo, Kwang-Kyu (Dept. of Management Engineering, Sangmyung Univ.)
Publication Information
Journal of the Semiconductor & Display Technology / v.20, no.2, 2021 , pp. 121-125 More about this Journal
Abstract
Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.
Keywords
Cloud; Cloud Service; Cloud Quality and Performance Management; Time Series Framework; T-framework; Bigdata; AI;
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