180 Works

CRAWDAD dataset microsoft/osdi2006 (v. 2007-05-23)

Ranveer Chandra, Ratul Mahajan, Venkat Padmanabhan & Ming Zhang
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.

CRAWDAD dataset sunysb/multi_channel (v. 2009-02-24)

Anand Prabhu Subramanian, Samir R. Das, Jing Cao & Chul Sung
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.

CRAWDAD dataset tools/analyze/pcap/WScout (v. 2010-01-13)

Thomas Claveirole & Marcelo Dias De Amorim
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.

CRAWDAD dataset nottingham/cattle (v. 2007-12-20)

Bartosz Wietrzyk & Milena Radenkovic
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.

CRAWDAD dataset nyupoly/video (v. 2014-05-09)

Fraida Fund, Cong Wang, Yong Liu, Thanasis Korakis, Michael Zink & Shivendra Panwar
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.

CRAWDAD dataset rice/ad_hoc_city (v. 2003-09-11)

Jorjeta G. Jetcheva, Yih-Chun Hu, Santashil PalChaudhuri, Amit Kumar Saha & David B. Johnson
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.

CRAWDAD dataset cu/lte (v. 2012-05-04)

Erik Bergal, Caleb Phillips & Chingpu Wu
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.

CRAWDAD dataset cu/antenna (v. 2009-05-08)

Eric W. Anderson & Caleb Phillips
We collected signal strength data to derive a parametric model for 2.4 GHz directional antennas.

CRAWDAD dataset uw/sigcomm2004 (v. 2005-08-01)

Maya Rodrig, Charles Reis, Ratul Mahajan, David Wetherall, John Zahorjan & Ed Lazowska
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.

CRAWDAD dataset rutgers/capture (v. 2007-04-20)

Kishore Ramachandran, Marco Gruteser, Ivan Seskar, Sachin Ganu & Jing Deng
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.

CRAWDAD dataset vanderbilt/interferometric (v. 2007-06-06)

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

CRAWDAD dataset tools/process/pcap/Wifipcap (v. 2008-02-01)

Jeffrey Pang
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.

CRAWDAD dataset tools/process/syslog/syslog_parser (v. 2006-11-01)

Tristan Henderson
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.

CRAWDAD dataset tools/collect/location/loctrace (v. 2007-09-14)

Thomas King, Stephan Kopf, Thomas Butter, Hendrik Lemelson, Thomas Haenselmann & Wolfgang Effelsberg
Loctrace is a research tool for 802.11-based positioning systems. Loctrace gathers data offered by Loclib and stores it in a file.

CRAWDAD dataset kth/rss (v. 2016-01-05)

Ramviyas Parasuraman, Sergio Caccamo, Fredrik Baberg & Petter Ogren
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).

CRAWDAD dataset ilesansfil/wifidog (v. 2015-11-06)

Michael Lenczner & Anne G. Hoen
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.

CRAWDAD dataset copelabs/usense (v. 2016-03-17)

S. Firdose, L. Lopes, W. Moreira, R. Sofia & P. Mendes
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.

CRAWDAD dataset iiitd/wifiactivescanning (v. 2019-06-05)

Gursimran Singh, Harish Fulara, Dheryta Jaisinghani, Mukulika Maity, Tanmoy Chakraborty & Vinayak Naik
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.

CRAWDAD dataset it/vr2marketbaiaotrial (v. 2019-09-16)

Ana Aguiar
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.

CRAWDAD dataset coppe-ufrj/RioBuses (v. 2018-03-19)

Daniel Dias & Luís Henrique Maciel Kosmalski Costa
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.

CRAWDAD dataset cmu/zigbee-smarthome (v. 2020-05-26)

Dimitrios-Georgios Akestoridis, Madhumitha Harishankar, Michael Weber & Patrick Tague
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...

CRAWDAD dataset queensu/crowd_temperature (v. 2015-11-20)

Mohannad A. Alswailim, Hossam S. Hassanein & Mohammad Zulkernine
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).

CRAWDAD dataset tools/process/pcap/WiPal (v. 2009-04-22)

Thomas Claveirole & Marcelo Dias De Amorim
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...

CRAWDAD dataset umd/sigcomm2008 (v. 2009-03-02)

Aaron Schulman, Dave Levin & Neil Spring
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.

CRAWDAD dataset tools/analyze/802.11/Wit (v. 2006-09-01)

Ratul Mahajan, Maya Rodrig & John Zahorjan
Wit is a non-intrusive tool that builds on passive monitoring to analyze the detailed MAC-level behavior of operational wireless networks.

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