Uninterruptible Data Supply for sustainable context aware system

Naoya Namatame, Jin Nakazawa, Kazunori Takashio, Hideyuki Tokuda

研究成果: Conference contribution

抄録

Various context mining algorithms are proposed aiming at improving accuracy. The major problem of the existing algorithms is that they assume no data loss in sensor data input, thus are unable to function sufficiently in a practical environment, where sensor data frequently drop. This paper proposes a novel middleware system called Uninterruptible Data Supply (UDS) system, which compensates the missing data with a probabilistic manner. Applications can benefit from UDS on the occurrence of constant and temporal deficit of sequential or discrete data. The evaluation shows that UDS can sustain the accuracy of context over 80% even with 40% data missing.

本文言語English
ホスト出版物のタイトルINSS 2010 - 7th International Conference on Networked Sensing Systems
ページ269-272
ページ数4
DOI
出版ステータスPublished - 2010 11月 12
イベント7th International Conference on Networked Sensing Systems, INSS 2010 - Kassel, Germany
継続期間: 2010 6月 152010 6月 18

出版物シリーズ

名前INSS 2010 - 7th International Conference on Networked Sensing Systems

Other

Other7th International Conference on Networked Sensing Systems, INSS 2010
国/地域Germany
CityKassel
Period10/6/1510/6/18

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 通信

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