last modified

2009-07-21

reason for most recent change

the initial version

release date

2009-07-23

date/time of measurement start

2006-08-26

date/time of measurement end

2008-04-18

website

netsrv.csc.ncsu.edu/twiki/bin/view/Main/MobilityModels

network type

GPS (Global Positioning System)

network type

DTN (Delay or Disruption Tolerant Network)

collection environment

Five sites are chosen for collecting human mobility traces. These are two university campuses (NCSU and KAIST), New York City, Disney World (Orlando), and North Carolina state fair.

network configuration

Garmin GPS 60CSx handheld receivers are used for data collection which are WAAS (Wide Area Augmentation System) capable with a position accuracy of better than three meters 95 percent of the time, in North America.

data collection methodology

The GPS receivers take reading of their current positions at every 10 seconds and record them into a daily track log.

limitation

Occasionally, track information has discontinuity mainly when bearers move indoor where GPS signals cannot be received.

note

The Campus I traces are taken by 20 students. The participants 
in Campus I were randomly selected students who took a course 
in the computer science department. Every week, 2 or 3 randomly 
chosen students carried the GPS receivers for their daily regular 
activities. 
The Campus II traces are taken by 32 students who live in a campus 
dormitory. 
The New York City traces were obtained from 12 volunteers living in 
Manhattan or its vicinity. Most of the participants have offices 
in Manhattan. Their track logs contain relatively long distance 
travels because of their long commuting paths. Their means of 
travel include subway trains, buses and mostly walking. 
The State fair track logs were collected from 8 volunteers who 
visited a local state fair that includes many street arcades, small 
street food stands and showcases. The event was very popular 
and attended by more than one thousand people daily for two 
weeks. The site is completely outdoor and is smallest among 
all the sites. Each participant in the State fair scenario spent 
less than three hours in the site. 
The Disney World traces were obtained from nineteen volunteers 
who spent their thanksgiving or Christmas holidays in Disney World, 
Florida, USA. For our study, we use only the track logs from 
the inside of the theme parks. The participants mainly walked 
in the parks and occasionally rode trolleys. 

• Injong Rhee
  rhee@ncsu.edu
  North Carolina State University
  Computer Science
  Associate Professor
  Department of computer Science North Carolina State University, NC 27606.
  www4.ncsu.edu/~rhee/
  
• Minsu Shin
  Hanoro Telecom
  
• Seongik Hong
  shong@ncsu.edu
  North Carolina State University
  Computer Science
  Ph.D Student
  2240 EBII Centennial Campus, North Carolina State University, Raleigh, NC 27695
  www4.ncsu.edu/~shong/
  
• Kyunghan Lee
  khlee@unist.ac.kr
  UNIST (Ulsan National Institute of Science and Technology)
  School of ECE
  Rm 301-5, EB 106, UNIST-gil 50, Ulsan, Korea
  sites.google.com/site/khanleepage/
  
• Seongjoon Kim
  North Carolina State University
  Computer Science
  Postdoc
  Department of computer Science North Carolina State University, NC 27606.
  
• Song Chong
  song@ee.kaist.ac.kr
  KAIST
  Electrical Engineering
  Professor
  School of EECS, KAIST, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon 305-701, Korea
  netsys.kaist.ac.kr/~song/
  

The following papers are written by the providers of this dataset who may be able to provide more information:

• On the Levy-Walk Nature of Human Mobility
  Injong Rhee; Minsu Shin; Seongik Hong; Kyunghan Lee; Seong J. Kim; Song Chong;
  IEEE/ACM Trans. Netw., Vol. 19, No. 3. (June 2011), pp. 630-643, doi:10.1109/tnet.2011.2120618.
• SLAW: A New Mobility Model for Human Walks
  Kyunghan Lee; Seongik Hong; Seong J. Kim; Injong Rhee; Song Chong;
  In INFOCOM 2009, IEEE (April 2009), pp. 855-863, doi:10.1109/infcom.2009.5061995.

163 papers using this dataset can be found in our CiteULike library.

When writing a paper that uses CRAWDAD datasets, we would appreciate it if you could cite both the authors of the dataset and CRAWDAD itself, and identify the exact dataset using the appropriate version number. For this dataset, this citation would look like:

Injong Rhee, Minsu Shin, Seongik Hong, Kyunghan Lee, Seongjoon Kim, Song Chong, CRAWDAD dataset ncsu/mobilitymodels (v. 2009‑07‑23), downloaded from https://crawdad.org/ncsu/mobilitymodels/20090723, https://doi.org/10.15783/C7X302, Jul 2009.

• Cite using BibTeX
• Cite using RIS

@misc{ncsu-mobilitymodels-20090723,
    author = {Injong Rhee and Minsu Shin and Seongik Hong and Kyunghan Lee and Seongjoon Kim and Song Chong},
    title = {{CRAWDAD} dataset ncsu/mobilitymodels (v. 2009-07-23)},
    howpublished = {Downloaded from \url{https://crawdad.org/ncsu/mobilitymodels/20090723}},
    doi = {10.15783/C7X302},
    month = jul,
    year = 2009
}

TY  - DATA
TI  - CRAWDAD dataset ncsu/mobilitymodels (v. 2009-07-23)
UR  - https://crawdad.org/ncsu/mobilitymodels/20090723
PY  - 2009/07/23/
AU  - Injong Rhee
AU  - Minsu Shin
AU  - Seongik Hong
AU  - Kyunghan Lee
AU  - Seongjoon Kim
AU  - Song Chong
DO  - 10.15783/C7X302
ER  -

If you do not use the provided citation formats, please include a reference with the same information, as described in the CRAWDAD FAQ.