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http://dx.doi.org/10.22156/CS4SMB.2021.11.05.023

The Method of Failure Management through Big Data Flow Management in Platform Service Operation Environment  

Baik, Song-Ki (Dept. of Computer Science & Engineering, Kongju National University)
Lim, Jae-Hyun (Dept. of Computer Science & Engineering, Kongju National University)
Publication Information
Journal of Convergence for Information Technology / v.11, no.5, 2021 , pp. 23-29 More about this Journal
Abstract
Recently, a situation in which a specific content service is impossible worldwide has occurred due to a failure of the platform service and a significant social and economic problem has been caused in the global service market. In order to secure the stability of platform services, intelligent platform operation management is required. In this study, big data flow management(BDFM) and implementation method were proposed to quickly detect to abnormal service status in the platform operation environment. As a result of analyzing, BDFM technique improved the characteristics of abnormal failure detection by more than 30% compared to the traditional NMS. The big data flow management method has the advantage of being able to quickly detect platform system failures and abnormal service conditions, and it is expected that when connected with AI-based technology, platform management is performed intelligently and the ability to prevent and preserve failures can be greatly improved.
Keywords
Platform management; Bigdata; Flow management; Platform services; Network management system;
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