CRAWDAD st_andrews/sassy

Encounter records of a group of participants carrying sensor motes and their social network data generated from Facebook data.This is a dataset of sensor mote encounter records and corresponding social network data of a group of participants at University of St Andrews. date/time of measurement start: 2008-02-15date/time of measurement end: 2008-04-29collection environment: We deployed 27 T-mote invent devices among human users associated with University of St Andrews. We could detect invent-to-invent encounters anywhere throughout the town of St Andrews and beyond.network configuration: We have set up a mobile sensor network comprising mobile IEEE 802.15.4 sensors (T-mote invent devices) carried by human users and Linux-based basestations that bridge the 802.15.4 sensors to the wired network. T-mote invent devices can detect each other within a radius of ~10m. These encounters are stored in the invent devices and are uploaded through the basestations to a central database. To upload encounters, we deployed three basestations across the two Computer Science buildings in our institution. data collection methodology: We deployed 27 T-mote invent devices among 22 undergraduate students, 3 postgraduate students, and 2 members of staff of University of St Andrews. Participants were asked to carry the devices whenever possible over a period of 79 days. The invent devices were programmed to broadcast a beacon every 6.67 seconds. When other devices (invent devices or basestations) detect these beacons, they record a timestamp and other information (such as signal strength) for this beacon. The timestamp, the device ID, and the other information form a Sensor Encounter Record (SER), which gets uploaded to a central database. We used the participants' Facebook friend lists to generate a social network topology. We refer to this as the self-reported social network (SRSN). We also generate a topology using the SERs to create the detected social network (DSN).sanitization: No record was made of mappings between device IDs and names of participants.limitation: To conserve storage on the invent devices, which only have 48 KB storage space, we only record the maximum, minimum, and mean measurements for encounters that last more than one polling interval.error: The upload times are assumed to be accurate - the error is maximum possible difference between the upload time and the start of the encounter. This is due to the clocks on the device not maintaining the previous clock time after a device reset or battery failure.Tracesetst_andrews/sassy/mobileEncounter records of a group of participants carrying sensor motes and their social network generated from Facebook data.files: dsn.csv.gz, srsn.csv.gzdescription: This is a dataset of sensor mote encounter records and corresponding social network data of a group of participants at University of St Andrews.measurement purpose: Routing Protocol for DTNs (Disruption Tolerant Networks), Social Network Analysis, Network Performance Analysis, Opportunistic Connectivitymethodology: We have set up a mobile sensor network comprising mobile IEEE 802.15.4 sensor (T-mote invent devices) carried by human users and Linux-based basestations that bridge the 802.15.4 sensors to the wired network. We deployed 27 T-mote invent devices among 22 undergraduate students, 3 postgraduate students, and 2 members of staff of University of St Andrews. Participants were asked to carry the devices whenever possible over a period of 79 days. We used the participants' Facebook friend lists to generate a social network topology. We refer to this as the self-reported social network (SRSN). We also generate a topology using the SERs to create the detected social network (DSN).st_andrews/sassy/mobile Tracesocial: This is a dataset of sensor mote encounter records and corresponding social network data of a group of participants at University of St Andrews.configuration: We have set up a mobile sensor network comprising mobile IEEE 802.15.4 sensors (T-mote invent devices) carried by human users and Linux-based basestations that bridge the 802.15.4 sensors to the wired network. The invent devices were programmed to broadcast a beacon every 6.67 seconds.format: The fields of dsn.csv are as follows:device_having_encounter - device that recorded the encounterdevice_seen - device that was detected rawtime_start - UNIX timestamp of encounter start rawtime_end - UNIX timestamp of encounter end timeuploaded - UNIX timestamp of when the encounter was uploaded to a basestation rssivalue - RSSI (max 256) errorval - error value of start time of encounter relative to upload time srsn.csv file contains a pairs of invent device IDs corresponding to Facebook friend connections.