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A Resource Trend Analysis from a Business Perspective Based on a Component Decomposition Approach

  • Yuji SaitohEmail author
  • Tetsuya Uchiumi
  • Yukihiro Watanabe
Conference paper
  • 4 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12403)

Abstract

To ensure reliability for information and communication technology (ICT) systems, it is important to analyze resource usage for the purpose of provisioning resources, detecting failures, and so on. It is more useful to understand the resource usage trends for each business process because generally multiple business processes run on an ICT system. For example, we can detect an increase in resource usage for a specific business process. However, conventional methods have not been able to analyze such trends because resource usage data is usually mixed and cannot be separated. Therefore, in the previous work, we proposed an analysis method that decomposes the data into components of each business process. The method successfully analyzed only single sources of data. However, an actual system consists of multiple resources and multiple devices. Therefore, in this paper, we enhance this method so that it is able to analyze multiple sources of data by incorporating a technique for unifying multiple sources of data into a single sources of data on the basis of a workload dependency model. In addition, the proposed method can also analyze the relationship between resources and application workloads. Therefore, it can identify specific applications that cause resource usage to increase. We evaluated the proposed method by using the data of on-premise and actual commercial systems, and we show that it can extract useful business trends. The method could extract system-wide processes, such as file-copy between two servers, and identify a business event corresponding to a resource usage increase.

Keywords

Non-negative matrix factorization Capacity provisioning Resource management IT operations management Business semantics 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yuji Saitoh
    • 1
    Email author
  • Tetsuya Uchiumi
    • 1
  • Yukihiro Watanabe
    • 1
  1. 1.Fujitsu Laboratories Ltd.KawasakiJapan

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