2nd International ICST Conference on Scalable Information Systems

Research Article

Exploiting Data Correlation for Multi-Scale Processing in Sensor Networks

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  • @INPROCEEDINGS{10.4108/infoscale.2007.899,
        author={Xiaoning Cui and Baohua Zhao and Qing Li},
        title={Exploiting Data Correlation for Multi-Scale Processing in Sensor Networks},
        proceedings={2nd International ICST Conference on Scalable Information Systems},
        proceedings_a={INFOSCALE},
        year={2010},
        month={5},
        keywords={Wireless sensor network Multi-scale processing Intra-/Inter-data correlation Data sample User query Correlation exploiting architecture Correlation adjustment function.},
        doi={10.4108/infoscale.2007.899}
    }
    
  • Xiaoning Cui
    Baohua Zhao
    Qing Li
    Year: 2010
    Exploiting Data Correlation for Multi-Scale Processing in Sensor Networks
    INFOSCALE
    ICST
    DOI: 10.4108/infoscale.2007.899
Xiaoning Cui1,2,3,*, Baohua Zhao1,2,*, Qing Li2,3,*
  • 1: Department of Computer Science and Technology, University of Science & Technology of China, Hefei, China
  • 2: Joint Research Lab of Excellence, CityU-USTC Advanced Research Institute, Suzhou, China
  • 3: Department of Computer Science, City University of Hong Kong, Hong Kong, China
*Contact email: cxning@mail.ustc.edu.cn, bhzhao@ustc.edu.cn, itqli@cityu.edu.hk

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.