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Performance Illustrations of the Developed Application Tool Based on Deep Learning

In: Applied OSS Reliability Assessment Modeling, AI and Tools

Author

Listed:
  • Yoshinobu Tamura

    (Yamaguchi University)

  • Shigeru Yamada

    (Tottori University)

Abstract

We focus on the OpenStack Project [1] which includes several edge components. In this chapter, we show numerical examples by using data sets on the assumption of the edge OSS service. The data used in this chapter are collected from the bug tracking system OpenStack Project [1]. The demonstration of our prototype tool is available from “DEMO APPLICATION” at the following URL; however, the function of calculation cannot execute considering the security: http://www.tam.eee.yamaguchi-u.ac.jp/ , accessed on 23 December 2023. Our prototype tool has been released as the OSS based on GNU General Public License (GPL) in December 2023. The source code of our tool is available from “SOFTWARE” at the following URL: http://www.tam.eee.yamaguchi-u.ac.jp/ , accessed on 23 December 2023.

Suggested Citation

  • Yoshinobu Tamura & Shigeru Yamada, 2024. "Performance Illustrations of the Developed Application Tool Based on Deep Learning," Springer Series in Reliability Engineering, in: Applied OSS Reliability Assessment Modeling, AI and Tools, chapter 0, pages 179-184, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-64803-8_11
    DOI: 10.1007/978-3-031-64803-8_11
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