Spatio-temporal Characteristics of Point and Field Sources in Wireless Sensor Networks


Vuran M. C., Akan O. B.

IEEE International Conference on Communications (ICC 2006), İstanbul, Türkiye, 11 - 15 Haziran 2006, ss.234-239 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icc.2006.254733
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.234-239
  • Anahtar Kelimeler: Spatio-temporal correlation, point source, field source, distortion, wireless sensor networks
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Wireless Sensor Networks (WSN) are comprised of densely deployed sensor nodes collaboratively observing and communicating extracted information about a physical phenomenon. Dense deployment of sensor nodes makes the sensor observations highly correlated in the space domain. In addition, consecutive samples obtained by a sensor node are also temporally correlated for the applications involving the observation of the variation of a physical phenomenon. Based on the physical characteristics and dispersion pattern over the area, the phenomenon to be observed can be modeled as point source or field source. Clearly, understanding the spatio-temporal correlation characteristics of the point and field sources brings potential advantages to be exploited in the design of efficient communication protocols. In this paper, a theoretical analysis of spatio-temporal correlation in WSN is carried out. The objective of this analysis is to capture the spatio-temporal characteristics of point and field sources in WSN. First, the model for point and field sources are developed and their spatio-temporal characteristics are analytically derived along with the distortion functions. Based on the theoretical analysis, numerical simulations are performed. This analytical work provides tools for finding the feasible operating region in terms of spatial and temporal resolution for a specific distortion constraint considering spatio-temporal correlation, signal properties, and network variables in WSN.