This project is no longer active; this page is no longer updated.
Related projects: [CRAWDAD], [DIST], [MAP], [Mobility-models], [NetSANI]
Related keywords: [wifi]
Wireless 802.11 (Wi-Fi) networks have become universal. In 2001, however, there were few large deployments and Dartmouth was one of the first universities to deploy a campus-wide Wi-Fi network. In 2001-02 we conducted the largest-ever characterization effort on a wireless network. In the initial effort we captured statistics and network traces from over 476 access points spread over 161 buildings at Dartmouth College, capturing the activity of nearly two thousand users. The original paper [kotz:campus] received the ACM SIGMOBILE Test-of-Time Paper Award in March 2017: "This paper was the first to systematically demonstrate how to measure and understand a production-scale wireless network, which was previously considered an impenetrable black box. This led to an incredible amount of follow-on work, with the measurement methods and analysis mechanisms proposed in this paper still being used. This paper was also the spark for the creation of the CRAWDAD data repository, which has been of immense value to the wireless research community."
Interested readers are directed to the journal paper [kotz:jcampus], however, for a more complete analysis and for some important corrections to the original results.
This work was described in a 2003 talk at Microsoft Research and a 2003 talk at Intel Research. (Apologies for the poor video quality -- they were transferred from VHS.)
The earliest (preliminary) report of this work was Pablo Stern's undergraduate thesis [stern:thesis].
We repeated the data-collection effort two years later and were able to measure trends and changes in network activity, as well as adding a new focus on VOIP and P2P traffic and on user mobility [henderson:jvoice, henderson:voice].
Along the way, we published methods for network measurement and analysis [henderson:measuring, henderson:esm].
Most recently (2019), We described and characterized the largest Wi-Fi network trace ever published: spanning seven years, approximately 3000 distinct access points, 40,000 authenticated users, and 600,000 distinct Wi-Fi stations. We described the methods used to capture and process the traces, and characterized the most prominent trends and changes during the seven-year span of the trace (2012-18). The analysis covers the same campus in the above papers, so we were able to comment on changes in patterns of usage, connection, and mobility in Wi-Fi deployments [camacho:longitudinal]. It also allowed us to explore methods for mining social interactions [martinez:poster].
We then applied the Multivariate Big Data Analysis (MBDA) methodology, a recently proposed interpretable data analysis tool in the detection and root-cause analysis of network anomalies. As a case study, we applied it a seven-year trace (from 2012 to 2018) of the Dartmouth Wi-Fi network's activity, with approximately 3,000 distinct access points, 40,000 authenticated users, and 600,000 distinct Wi-Fi stations [camacho:networkmetrics-j], with earlier versions of that work appearing as [camacho:networkmetrics, camacho:networkmetrics-tr, camacho:networkmetrics-tr2].
In 2004 we released the earliest data and founded CRAWDAD.org, a "Community Resource for Archiving Wireless Data at Dartmouth", to encourage broader sharing of such data across the research community.
We also mined the original data for many other studies -- see the list of related projects and keywords above, as well as some related projects [lee:thesis, mills:tettey-thesis].
In 2021, we proposed a system that, in a preliminary evaluation, was able to decide with 82% accuracy whether the location of an IoT device is inside or outside of a defined space based on a small number of transmitted Wi-Fi frames. See Paul Gralla's undergraduate thesis for details [gralla:inside-outside].
The following people were involved in wireless-data collection at Dartmouth: Denise Anthony, Ilya Abyzov, David Blinn, Guanling Chen, Kobby Essien, Jeff Fielding, Paul Gralla, Tristan Henderson, David Kotz, Nathan Schneider, and Pablo Stern.
In addition to the above people, the following were co-author on one or more papers listed below: Rasmus Bro, Elena Cabrera, José Camacho, Eduardo Antonio Mañas-Martínez, and Katarzyna Wasielewska.
Each of the works described on this page were supported by one or more of the following sponors: Cisco Systems, Dartmouth Institute for Security Technology Studies (ISTS), DoCoMo USA Labs, Intel Corporation, the US National Science Foundation under Infrastructure Award number EIA-9802068, the US Department of Justice (Bureau of Justice Assistance) under award 2005-DD-BX-1091, and the US Department of Homeland Security (Science and Technology Directorate) under Award Number 2000-DT-CX-K001.
The CRAWDAD archive, which resulted from this work and which was the source of data for many papers in this work, was funded by the National Science Foundation under award number 0454062.
Author José Camacho was supported by the US Fulbright Scholars Program. He was also supported by the Ministerio de Educación, Cultura y Deporte under the Programa Estatal de Promoción de Talento y su Empleabilidad en I+D+i, Subprograma Estatal de Movilidad, del Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016, grant number PRX17/00320 (associated to a Fulbright Scholarship); and the Plan Propio de la Universidad de Granada, grant number PP2017.VS.02.
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In this poster we report preliminary work in which we infer social interactions of individuals from Wi-Fi connection traces in the campus network at Dartmouth College. We make the following contributions: (i) we propose several definitions of a pseudocorrelation matrix from Wi-Fi connection traces, which measure similarity between devices or users according to their temporal association profile to the Access Points (APs); (ii) we evaluate the accuracy of these pseudo-correlation variants in a simulation environment; and (iii) we contrast results with those found on a real trace.
We found that the applications used on the WLAN changed dramatically, with significant increases in peer-to-peer and streaming multimedia traffic. Despite the introduction of a Voice over IP (VoIP) system that includes wireless handsets, our study indicates that VoIP has been used little on the wireless network thus far, and most VoIP calls are made on the wired network.
We saw greater heterogeneity in the types of clients used, with more embedded wireless devices such as PDAs and mobile VoIP clients. We define a new metric for mobility, the “session diameter”. We use this metric to show that embedded devices have different mobility characteristics than laptops, and travel further and roam to more access points. Overall, users were surprisingly non-mobile, with half remaining close to home about 98% of the time.
In this chapter we discuss the measurement and analysis of the popular 802.11 family of wireless LANs. We describe the tools, metrics and techniques that are used to measure wireless LANs. The results of existing measurement studies are surveyed. We illustrate some of the problems that are specific to measuring wireless LANs, and outline some challenges for collecting future wireless traces.
We found that residential traffic dominated all other traffic, particularly in residences populated by newer students; students are increasingly choosing a wireless laptop as their primary computer. Although web protocols were the single largest component of traffic volume, network backup and file sharing contributed an unexpectedly large amount to the traffic. Although there was some roaming within a network session, we were surprised by the number of situations in which cards roamed excessively, unable to settle on one access point. Cross-subnet roams were an especial problem, because they broke IP connections, indicating the need for solutions that avoid or accommodate such roams.
This paper analyzes an extensive network trace from a mature 802.11 WLAN, including more than 550 access points and 7000 users over seventeen weeks. We employ several measurement techniques, including syslogs, telephone records, SNMP polling and tcpdump packet sniffing. This is the largest WLAN study to date, and the first to look at a large, mature WLAN and consider geographic mobility. We compare this trace to a trace taken after the network’s initial deployment two years ago.
We found that the applications used on the WLAN changed dramatically. Initial WLAN usage was dominated by Web traffic; our new trace shows significant increases in peer-to-peer, streaming multimedia, and voice over IP (VoIP) traffic. On-campus traffic now exceeds off-campus traffic, a reversal of the situation at the WLAN’s initial deployment. Our study indicates that VoIP has been used little on the wireless network thus far, and most VoIP calls are made on the wired network. Most calls last less than a minute.
We saw greater heterogeneity in the types of clients used, with more embedded wireless devices such as PDAs and mobile VoIP clients. We define a new metric for mobility, the “session diameter.” We use this metric to show that embedded devices have different mobility characteristics than laptops, and travel further and roam to more access points. Overall, users were surprisingly non-mobile, with half remaining close to home about 98% of the time.
In this study, we begin with a large outdoor routing experiment testing the performance of four popular ad hoc algorithms (AODV, APRL, ODMRP, and STARA). We present a detailed comparative analysis of these four implementations. Then, using the outdoor results as a baseline of reality, we disprove a set of common assumptions used in simulation design, and quantify the impact of these assumptions on simulated results. We also more specifically validate a group of popular radio models with our real-world data, and explore the sensitivity of various simulation parameters in predicting accurate results. We close with a series of specific recommendations for simulation and ad hoc routing protocol designers.
We found that the applications used on the WLAN changed dramatically. Initial WLAN usage was dominated by Web traffic; our new trace shows significant increases in peer-to-peer, streaming multimedia, and voice over IP (VoIP) traffic. On-campus traffic now exceeds off-campus traffic, a reversal of the situation at the WLAN’s initial deployment. Our study indicates that VoIP has been used little on the wireless network thus far, and most VoIP calls are made on the wired network. Most calls last less than a minute.
We saw more heterogeneity in the types of clients used, with more embedded wireless devices such as PDAs and mobile VoIP clients. We define a new metric for mobility, the “session diameter.” We use this metric to show that embedded devices have different mobility characteristics than laptops, and travel further and roam to more access points. Overall, users were surprisingly non-mobile, with half remaining close to home about 98% of the time.
We found that most of the users of Dartmouth's network have short association times and a high rate of mobility. This observation fits with the predominantly student population of Dartmouth College, because students do not have a fixed workplace and are moving to and from classes all day.
We found that residential traffic dominated all other traffic, particularly in residences populated by newer students; students are increasingly choosing a wireless laptop as their primary computer. Although web protocols were the single largest component of traffic volume, network backup and file sharing contributed an unexpectedly large amount to the traffic. Although there was some roaming within a network session, we were surprised by the number of situations in which cards roamed excessively, unable to settle on one access point. Cross-subnet roams were an especial problem, because they broke IP connections, indicating the need for solutions that avoid or accommodate such roams.
We found that residential traffic dominated all other traffic, particularly in residences populated by newer students; students are increasingly choosing a wireless laptop as their primary computer. Although web protocols were the single largest component of traffic volume, network backup and file sharing contributed an unexpectedly large amount to the traffic. Although there was some roaming within a network session, we were surprised by the number of situations in which cards roamed excessively, unable to settle on one access point. Cross-subnet roams were an especial problem, because they broke IP connections, indicating the need for solutions that avoid or accommodate such roams.
We found that residential traffic dominated all other traffic, particularly in residences populated by newer students; students are increasingly choosing a wireless laptop as their primary computer. Although web protocols were the single largest component of traffic volume, network backup and file sharing contributed an unexpectedly large amount to the traffic. Although there was some roaming within a network session, we were surprised by the number of situations in which cards roamed excessively, unable to settle on one access point. Cross-subnet roams were an especial problem, because they broke IP connections, indicating the need for solutions that avoid or accommodate such roams.
We present the design of Mobile Voice over IP (MVOIP), an application-level protocol that enables such mobility in a VOIP application based on the ITU H.323 protocol stack. An MVOIP application uses hints from the surrounding network to determine that it has switched subnets. It then initiates a hand-off procedure that comprises pausing its current calls, obtaining a valid IP address for the current subnet, and reconnecting to the remote party with whom it was in a call. Testing the system shows that on a Windows 2000 platform there is a perceivable delay in the hand-off process, most of which is spent in the Windows API for obtaining DHCP addresses. Despite this bottleneck, MVOIP works well on a wireless network.