Uninterruptible Data Supply for sustainable context aware system

Naoya Namatame, Jin Nakazawa, Kazunori Takashio, Hideyuki Tokuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationINSS 2010 - 7th International Conference on Networked Sensing Systems
Pages269-272
Number of pages4
DOIs
Publication statusPublished - 2010 Nov 12
Event7th International Conference on Networked Sensing Systems, INSS 2010 - Kassel, Germany
Duration: 2010 Jun 152010 Jun 18

Publication series

NameINSS 2010 - 7th International Conference on Networked Sensing Systems

Other

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

Keywords

  • Context-aware system
  • Dependable system
  • Sensor network

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Communication

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