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Exploiting data correlation for multi-scale processing in sensor networks

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

With the emergence of large and multi-scale sensor networks, the technologies of multi-scale processing among various sensors become an essential issue. In this paper, the problem of exploiting data correlation for multi-scale sensor networks is considered, and an architecture exploiting correlation is designed for both intraand inter-data processing. Our correlation-adaptive scheme follows the characteristics of real sensor data, and fills the gap of the correlation models addressed by most of previous research with inherent support for related data gathering algorithms. A core solution module of this architecture is devised, and theoretical analysis and simulation studies are conducted on real-world datasets. Through the real-world data experiments in terms of accuracy and energy-consumption evaluation, the correlationadaptive scheme is shown to work well in multi-scale processing sensor networks. © 2007 ICST
Original languageEnglish
Title of host publication2nd International ICST Conference on Scalable Information Systems
EditorsLiusheng Huang, Dov Dori , Qing Li
PublisherICST
Number of pages8
ISBN (Print)9781595937575
DOIs
Publication statusPublished - Jun 2007
Event2nd International Conference on Scalable Information Systems (InfoScale 2007) - Suzhou, China
Duration: 6 Jun 20078 Jun 2007

Publication series

NameACM International Conference Proceeding Series (ACM ICPS)

Conference

Conference2nd International Conference on Scalable Information Systems (InfoScale 2007)
PlaceChina
CitySuzhou
Period6/06/078/06/07

Research Keywords

  • Correlation adjustment function
  • Correlation exploiting architecture
  • Data sample
  • Intra-/inter-data correlation
  • Multi-scale processing
  • User query
  • Wireless sensor network

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