Data & Tools

Both data and software tools are publicly available from current and past research. In addition to our public data sets, please visit CRAWDAD, a sizeable and growing worldwide repository of measured data sets dealing generally with wireless networks. In particular, the SPAN lab collaboratively maintains the CRAWDAD Channel Area Wiki, a cross-listing of physical and channel-layer data sets within and outside of CRAWDAD.

Public Data Sets

Public Tools

  • NeSh Model : Code is available for the simulation of the Network Shadowing (NeSh) model. The Matlab code uses given sensor coordinates and model parameters to calculate the covariance matrix for the path losses measured on each link in a network. This covariance matrix can then be used, as it is in the example script included, to generate realizations of correlated path loss on all links in a network. It can be used to simulate connectivity, capacity, or other performance metrics (Agrawal 09 and Patwari & Agrawal 08).
  • Map-tools: A C-based toolset applies non-linear dimension reduction techniques to internet traffic visualization, as a means to identify anomalies such as port scans and DoS attacks.
  • Cooperative Localization Matlab Code: This code implements both the maximum likelihood estimator described in (Patwari 03), and the Cramer-Rao lower bound presented in (Patwari 05).
  • Spin: NesC/TinyOS 2.x code for collecting RSS measurements in a wireless network. Utilizes a token passing protocol to prevent collisions in large networks that transmit many packets.

TinyOS Search Engine

This is a custom Google search engine that only returns results from pages that are directly related to the TinyOS operating system. Use this box to find help and information quickly.

SPAN Beamer Template

This is a Beamer template with the SPAN logo, U of Utah logo and a navigation bar on top. Please replace the .pdf file extension with .zip and read the sample.pdf file before using the template.