10 Works

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 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 buffalo/phonelab-wifi (v. 2016-03-09)

Jinghao Shi, Chunming Qiao, Dimitrios Koutsonikolas & Geoffrey Challen
Smartphones perform Wifi scans to adapt to the changing wireless environments causes by mobility. From network monitoring perspective, such scans provide a natural stream of network measurements from client's point of view. In order to see whether such measurements can provide new insights in monitoring large scale wireless networks, we collected the Wifi scan results data, together with other Wifi related logs, from the PhoneLab smartphone testbed over 5 months. All data are collected passively...

CRAWDAD dataset init/factory (v. 2016-06-13)

Dimitri Block, Niels Hendrik Fliedner & Uwe Meier
Measurement of the channel gain for multiple distances within a factory environment

CRAWDAD dataset oviedo/asturies-er (v. 2016-04-12)

Sergio Cabrero, Roberto Garcia, Xabiel G. Garcia & David Melendi
This dataset contains ONE connectivity traces extracted from GPS traces collected from the regional Fire Department of Asturias, Spain. The original data source is one year of GPS traces extracted from a Geographical Information System (GIS). The traces were generated by GPS devices embedded mainly in cars and trucks, but also in a helicopter and a few personal radios. A total of 229 devices reported 19,462,339 locations. A new location is reported with an interval...

CRAWDAD dataset oviedo/asturies-er (v. 2016-08-08)

Sergio Cabrero, Roberto García, Xabiel G. García & David Melendi
This dataset contains mobility and connectivity traces extracted from GPS traces collected from the regional Fire Department of Asturias, Spain. The original data source is one year of GPS traces extracted from a Geographical Information System (GIS). The traces were generated by GPS devices embedded mainly in cars and trucks, but also in a helicopter and a few personal radios. A total of 229 devices reported 19,462,339 locations. A new location is reported with an...

CRAWDAD dataset tools/simulate/uoi/adyton (v. 2016-04-21)

Nikolaos Papanikos, Dimitrios-Georgios Akestoridis & Evangelos Papapetrou
Adyton is an event-driven network simulator, written in C++, for Opportunistic Networks (a.k.a. Delay-Tolerant Networks) that is capable of processing contact traces. The Adyton simulator supports a plethora of routing protocols and real-world contact traces, while also providing several congestion control mechanisms and buffer management policies.

CRAWDAD dataset uoi/haggle (v. 2016-08-28)

Dimitrios-Georgios Akestoridis
This dataset contains seven connectivity traces that have been derived from the cambridge/haggle/imote traceset (v. 2009-05-29). These connectivity traces can be used for network simulations with the Opportunistic Network Environment (ONE) simulator, since they are in accordance with the syntax of the StandardEventsReader format. The Python scripts that generated these connectivity traces are also provided.

CRAWDAD dataset upb/hyccups (v. 2016-10-17)

Radu I. Ciobanu & Ciprian Dobre
Wireless contacts trace collected at the University Politehnica of Bucharest in the spring of 2012, using an application entitled HYCCUPS Tracer (http://hyccups.hpc.pub.ro), with the purpose of collecting contextual data from Android smartphones. It was run in the background and collected availability and mobile interaction information such as usage statistics, user activity, battery statistics, or sensor data, but it also gathered information about a device's encounters with other nodes or with wireless access points. Encounter collection...

CRAWDAD dataset uclouvain/mptcp_smartphone (v. 2016-03-04)

Quentin De Coninck, Matthieu Baerts, Benjamin Hesmans & Olivier Bonaventure
Multipath TCP is a recent TCP extension that enables multihomed hosts like smartphones to send and receive data over multiple interfaces. Despite the growing interest in this new TCP extension, little is known about its behavior with real applications in wireless networks. Our paper "A First Analysis of Multipath TCP on Smartphones" analyzes a trace from a SOCKS proxy serving smartphones using Multipath TCP. This first detailed study of real Multipath TCP smartphone traffic reveals...

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