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
- Measured MIMO channel impulse response (CIR) data used in the paper, Experimental performance evaluation of location distinction for MIMO links, by D. Maas, N. Patwari, S.K. Kasera, D. Wasden, and M. Jensen, which appeared in the Proc. 4th IEEE International Conference on Communication Systems and Networks (COMSNETS) 2012.
- Measured channel impulse response (CIR) in an indoor wireless sensor network: These measurements were initially reported in (Patwari 03), but only RSS and TOA were utilized. For a Mobicom 2007 paper, this set of complex impulse response measurements was used for location distinction. This data set is posted and discussed on the Measured CIR Data Set page.
- Measurements of received signal strength (RSS) and time-of-arrival (TOA) in an indoor wireless sensor network were made publicly available in July 2005. This data set comprises pair-wise measurements in a 44-node network originally reported in (Patwari 03).
- Radio Tomographic Imaging Data Set - Data from an outdoor RTI experiment consisting of 28 network nodes arranged in a square. The data is in easy-to-read csv files.
- Kernel Distance-Based Radio Tomographic Imaging (KRTI) Data Set - Data from two through-wall experiments under noisy conditions. The KRTI paper can be found here, while the data with a readme file is here.
- 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.