機械学習を用いた一般トラヒック型待ち行列システムの性能評価

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2019/01/01

タイトル(英語): A Performance Evaluation of General Queueing Systems by Machine Learning

著者名: 二井　克（愛知県立大学 大学院 情報科学研究科），奥田　隆史（愛知県立大学 情報科学部 情報科学科）

著者名(英語): Suguru Nii (Graduate School of Information Science and Technology, Aichi Prefectual University), Takashi Okuda (Department of Information Science and Technology, Faculty of Information Science and Technology, Aichi Prefectural University)

キーワード: IoT (Internet of Things)，待ち行列システム，機械学習　　IoT (Internet of Things)，queueing systems，machine learning

要約(英語): This paper presents a method for performance evaluation of general queueing systems that is important for designing IoT (Internet of Things) data processing systems. IoT has been paid great attention all over the world. There are a lot of IoT devices that connect Internet. In addition, IoT devices are many kinds. Hence, IoT data processing systems have to handle massive, many kinds of data. From the above, when we design IoT data processing systems, it is important to evaluate performance of general queueing systems. However, in general queueing systems, the exact solution that can evaluate performance is not available. Alternatively, we can evaluate it with discrete simulation. However, it spends much time. From the above reasons, we evaluate performance of general queueing systems by machine learning instead of discrete simulation. In addition, we validate what kind of teacher data we should use for machine learning.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.139 No.1 （2019） 特集：電子回路関連技術

本誌掲載ページ: 98-105 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/139/1/139_98/_article/-char/ja/