Stream-based real world information integration framework

Hiroyuki Kitagawa, Yousuke Watanabe, Hideyuki Kawashima, Toshiyuki Amagasa

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)


For real world oriented applications to easily use sensor data obtained frommultiple wireless sensor networks, a data management infrastructure is mandatory. The infrastructure design should be based on the philosophy of a novel framework beyond the relational data management for two reasons: First is the freshness of data. To keep sensor data fresh, an infrastructure should process data efficiently; this means conventional time consuming transaction processing methodology is inappropriate. Second is the diversity of functions. The primary purpose of sensor data applications is to detect events; unfortunately, relational operators contribute little toward this purpose. This chapter presents a framework that directly supports efficient processing and a variety of advanced functions. Stream processing is the key concept of the framework. Regarding the efficiency requirement, we present a multiple query optimization technique for query processing over data streams; we also present an efficient data archiving technique. To meet the functions requirement, we present several techniques on event detection, which include complex event processing, probabilistic reasoning, and continuous media integration.

Original languageEnglish
Title of host publicationWireless Sensor Network Technologies for the Information Explosion Era
EditorsTakahiro Hara, Erik Buchmann, Vladimir Zadorozhny
Number of pages32
Publication statusPublished - 2010
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence


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