Research on big data magnifying glasses for data processing considering urgency

2018 Fiscal Year Final Research Report

• Project/Area Number: 16K12411
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Software
• Research Institution: The University of Electro-Communications
• Principal Investigator: Akihiko Ohsuga 電気通信大学, 大学院情報理工学研究科, 教授 (90393842)
• Co-Investigator(Kenkyū-buntansha): 田原 康之 電気通信大学, 大学院情報理工学研究科, 准教授 (30390602) ; 清 雄一 電気通信大学, 大学院情報理工学研究科, 准教授 (20700157)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: ソフトウェア工学 / ビッグデータ / ソーシャルメディア / プライバシ保護 / クラウドコンピューティング / 自己適応システム / 機械学習 / 差分プライバシ

Outline of Final Research Achievements

In this research, we developed a big data processing middleware that enables the construction of systems that adapt to changing urgency levels by changing the degree of abstraction of the data and the degree of protection of the privacy according to the local degree of urgency determined automatically, as if you moved the magnifying glass up and down and left and right to look at the data. For this purpose, we established data abstraction level adjustment method and privacy protection degree adjustment method, constructed an architecture to switch these layers according to the level of urgency, integrated it as middleware with an interface that imitates the operation of the magnifying glass to handle the change of level of urgency, developed a big data application example, evaluated it experimentally, and published the results.

Free Research Field

エージェント技術，ソフトウェア工学

Academic Significance and Societal Importance of the Research Achievements

本研究の成果は，広範囲なビッグデータ活用において，緊急度に応じて適切な処理が人手を介することなく可能となるため，各種のアプリケーションやサービスの構築と運用のコストを抑えながら，付加価値を大いに高めることにより，多大な社会的インパクトをもたらすものと考えられる．