Projects: High Resolution Signal Reconstruction

Apart from the traditional low data rate applications implemented in sensor networks, a need of supporting higher data rate applications, such as audio and video streaming, has appeared lately. Specifically, there is a lot of interest in real-time streaming for military surveillance purposes and for emergency situations. The lack of bandwidth and limited sampling rate capabilities of sensors render the implementation of these applications challenging. Among the requirements of streaming applications is the high volume of data that needs to be sent to the sink. The basic drawback of obtaining data from one particular node every time is that it could lead to an over-utilization of the radio of specific nodes. The radio is one of the most energyinefficient component on a sensor and power supply is limited and battery recharging is almost inexistent. This eventually leads to depletion of the power supply of those nodes sooner than the other ones and reduces significantly the network lifetime. Another factor to take into consideration is that, in WSNs, the data from neighboring nodes is usually highly correlated. Consequently, the transmission of the gathered data of those nodes leads to redundant information. Our aim is to design a distributed scheme for data acquisition that balances energy consumption while exploiting spatial correlations between neighboring nodes. In the process, we also reduce the bandwidth and processing requirements for sensor nodes.

Members

  • Andria Pazarloglou (PhD student)
  • George, Mike (PhD student)
  • Radu Stoleru (faculty)
  • Ricardo Gutierrez-Ossuna (faculty, collaborator)

Papers

  • S. M. George, W. Zhou, H. Chenji, M. Won, Y.-Oh Lee, A. Pazarloglou, R. Stoleru, P. Barooah, "DistressNet: a Wireless AdHoc and Sensor Network Architecture for Situation Management in Disaster Response," In IEEE Communications, 2010
  • A. Pazarloglou, R. Stoleru, R. Gutierrez-Osuna, "High-resolution speech signal reconstruction in Wireless Sensor Networks," in Proceedings of IEEE Workshop on Information Retrieval in Sensor Networks (IRSN), 2009
  • A. Pazarloglou, M. George, R. Stoleru, R. Gutierrez-Osuna, "Demo Abstract: Signal Reconstruction with SubNyquist Sampling using Wireless Sensor Networks," in Proceedings of ACM/IEEE Information Processing in Sensor Networks (IPSN), 2009

Source Code Releases

  • High resolution signal reconstruction release 1.0 (Matlab and TinyOS code)