The authors gathered a detailed trace of network activity at OSDI 2006 to enable analysis of the behavior of a wireless LAN that is (presumably) heavily used.

We conduct measurement using two mesh network testbeds in two different frequency bands – 802.11g in 2.4GHz band and 802.11a in 5GHz band.

WScout provides a PCAP traces visualizer that is able to work with huge traces (>10 GiB). Its goals are speed and low memory requirements. Despite its design being protocol-agnostic, it currently handles only Prism and IEEE 802.11 headers, hence its name.

We performed the field experiments of cattle movement and behavior monitoring at the University of Nottingham's Dairy Centre to collect realistic parameters necessary to develop and evaluate an adequate wireless protocol.

This dataset describes measurements from Dynamic Adaptive Streaming over HTTP (DASH) and WebRTC video services, collected over the GENI WiMAX networks at NYU-Poly and UMass Amherst. These measurements are meant to elucidate the experience of an individual user of these services who is moving at walking speeds through the coverage area of a typical cellular network.

We acquired several weeklong traces of the movement of the fleet of city buses in Seattle, Washington, on their normal routes providing passenger bus service throughout the city.

This data was collected at the University of Colorado Boulder. It contains careful point measurements, taken on a 100m equilateral triangular lattice, of the Verizon LTE network.

We collected signal strength data to derive a parametric model for 2.4 GHz directional antennas.

We are trying to understand how well 802.11 networks work in practice and how they can be improved. This dataset includes the traces collected by wireless monitoring and wired monitoring using tcpdump.

In an experiment involving two senders and one receiver, we placed a sniffer (wireless NIC in monitor mode) close to each of the senders so as to capture all transmitted MAC frames from each sender.

We collected localization traces from a radio interferometric tracking system, which is implemented on mote-class wireless sensor nodes.

A simple C++ wrapper around libpcap that allows applications to selectively demultiplex 802.11 frames, and the most common layer 2 and layer 3 protocols contained within them. Basically, the wifipcap library handles all the parsing of 802.11 frames (and/or layer 2/3 packets) from the pcap file (or stream). wifipcap is now embedded in tcpflow, a TCP/IP session reassembler maintained by Simson Garfinkel.

syslog_parser is a script to parse the syslog traces from Cisco VxWorks, Cisco IOS and Aruba access points. This script was designed to parse the syslog traces in the dartmouth/campus/syslog tracesets, but should be useful for other traces as well.

Loctrace is a research tool for 802.11-based positioning systems. Loctrace gathers data offered by Loclib and stores it in a file.

This dataset contains the RSS (Radio Signal Strength) data collected with a mobile robot in two environments: indoor (KTH) and outdoor (Dortmund). RSSI metric was used to collect the RSS data in terms of dBm. The mobile robot location was recorded using its odometry (dead reckoning).

This data set contains user session traces which were collected from a large number of free Wi-Fi hotspots in Montreal, Quebec, Canada for six years.

This data set comprises experiments carried out considering four Android devices, each named Usense 2, 3, 4, and 5, respectively. These devices were carried by people sharing the same affiliation during their daily routines (commuting between home and office, going to leisure activities, attending meetings in the office). All the data was collected each and every one minute.

The dataset includes packet captures collected from controlled experiments with various devices. The dataset captures active scanning behavior of the devices. Name of each folder represents the name of the cause of active scanning. For details please refer to our papers - Learning to Rescue WiFi Networks from Unnecessary Active Scans, WoWMoM 2019.

Dataset that contains simultaneous GPS traces collected at 1 Hz from a team of firefighters during a forest fire exercise. The traces were generated by Android phones placed in each of four firefighters and a generic GPS device placed in the firetruck.

Real-time position data reported by buses, updated every minute, from the city of Rio de Janeiro, Brazil. The file is CSV, containing the date, time(24h format), bus ID, bus line, latitude, longitude and speed of more than 12,000 buses.

This Carnegie Mellon University dataset contains Zigbee packets that were captured using a software-defined radio (USRP N210). More specifically, the contributors used GNU Radio with the gr-ieee802-15-4 and gr-foo modules to receive IEEE 802.15.4 packets and store them in PCAP format. The captured network traffic was generated from ten commercial Zigbee devices that can be found in smart home environments. Eight experiments were conducted that differed in the smart hub that was used and the...

This dataset is to be used in conjunction with the roma/taxi dataset and provides the outdoor temperature of the areas in Rome where the taxis were located (289 taxicabs over 4 days).

WiPal is a piece of software dedicated to IEEE 802.11 traces manipulation. It comes as a set of programs and a C++ library. A distinctive feature of WiPal is its merging tool, which enables merging multiple wireless traces into a unique global trace. This tool works offline on PCAP traces that do not need to be synchronized. WiPal also provides statistics extraction and anonymization tools, and its authors plan to extend it. WiPal’s key features...

We collected a trace of wireless network activity at SIGCOMM 2008. The subjects of the traced network chose to participate by joining the traced SSID. The release contains 3 types of anonymized traces: 802.11a, Ethernet and Syslog from the Access Point. We anonymized the trace data using a modified version (http://www.cs.umd.edu/projects/wifidelity/sigcomm08_traces/sigcomm08-tcpmkpub.tar.gz) of the tcpmkpub tool (http://www.icir.org/enterprise-tracing/tcpmkpub.html) The packet traces include anonymized DHCP and DNS headers.

Wit is a non-intrusive tool that builds on passive monitoring to analyze the detailed MAC-level behavior of operational wireless networks.