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Data Alignment for Data Fusion in Wireless Multimedia Sensor Networks Based on M2M

  • Cruz, Jose Roberto Perez (Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE)) ;
  • Hernandez, Saul E. Pomares (Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE)) ;
  • Cote, Enrique Munoz De (Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE))
  • Received : 2011.08.31
  • Accepted : 2011.11.28
  • Published : 2012.01.30

Abstract

Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

Keywords

References

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