Density-Based Data Selection and Management for Edge Computing

Hiroki Oikawa, Masaaki Kondo

研究成果: Conference contribution

抄録

Wide spread of IoT devices has made it possible to acquire enormous amounts of realtime sensor information. Due to the explosive increase in the sensing data volume, it becomes difficult to collect and process all the data in one central place. On one hand, storing and processing data on edge devices, so called edge computing, is becoming important. On the other hand, edge devices usually have only limited computing and memory resources, and hence it is not practical to process and save all the acquired data. There is a great demand of effectively selecting data to process on an edge device or to transfer it to a cloud server. In this paper, we propose an efficient density-based data selection and management method called O-D2M by which edge devices store the data representing inherent data distribution. We use a low cost graph algorithm to analyze input data trend and its density. We evaluate effectiveness of the proposed O-D2M comparing to other methods in terms of the accuracy of machine learning models trained by the selected data. Throughout the evaluation, we confirm that O-D2M obtains higher accuracy and lower computation cost while it can reduce the amount of data to be processed or transferred by up to 20 points.

本文言語English
ホスト出版物のタイトル2021 IEEE International Conference on Pervasive Computing and Communications, PerCom 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781665404181
DOI
出版ステータスPublished - 2021 3 22
外部発表はい
イベント19th IEEE International Conference on Pervasive Computing and Communications, PerCom 2021 - Virtual, Kassel, Germany
継続期間: 2021 3 222021 3 26

出版物シリーズ

名前2021 IEEE International Conference on Pervasive Computing and Communications, PerCom 2021

Conference

Conference19th IEEE International Conference on Pervasive Computing and Communications, PerCom 2021
国/地域Germany
CityVirtual, Kassel
Period21/3/2221/3/26

ASJC Scopus subject areas

  • 情報システムおよび情報管理
  • 電子工学および電気工学
  • 器械工学
  • 技術マネージメントおよび技術革新管理
  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識

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