Analysis of User Mobility Models Based on Outdoor Measurement Data and Literature Surveys
Baloch, Shahbaz Hussain (2014)
Baloch, Shahbaz Hussain
2014
Master's Degree Programme in Information Technology
Teknisten tieteiden tiedekunta - Faculty of Engineering Sciences
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
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Hyväksymispäivämäärä
2014-12-03
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201412011558
https://urn.fi/URN:NBN:fi:tty-201412011558
Tiivistelmä
The main objectives of the presented work are to study the various existing human mobility models based on literature reviews and to select an appropriate and simplified mobility model fit to the available measurement data. This thesis work is mainly processing a part of “Big Data” that was collected from large number of people, known as Mobile Data Challenge (MDC). MDC is large scale data collection from Smartphone based research.
The thesis also addressed the fact that appropriate mobility models could be utilized in many important practical applications, such as in public health care units, for elderly care and monitoring, to improve the localization algorithms, in cellular communications networks to avoid traffic congestion, for designing of such systems that can predict prior users location, in economic forecasting, for public transportation systems and for developing social mobile applications.
Basically, mobility models indicate the movement patterns of users and how their position, velocity and acceleration vary with respect to time. Such models can be widely used in the investigation of advanced communication and navigation techniques. These human mobility models are normally classified into two main models, namely; entity mobility models and group mobility models. The presented work focuses on the entity mobility models.
The analysis was done in Matlab, based on the measurement data available in MDC database, the several parameters of Global Positioning System (GPS) data were extracted, such as time, latitude, longitude, altitude, speed, horizontal accuracy, horizontal Dilution of Precision (DOP), vertical accuracy, vertical DOP, speed accuracy etc. Parts of these parameters, namely the time, latitude, longitude, altitude and speed were further investigated in the context of basic random walk mobility model.
The data extracted from the measurements was compared with the 2-D random walk mobility model. The main findings of the thesis are that the random walk model is not a perfect fit for the available user measurement data, but can be used as a starting point in analyzing the user mobility models.
The thesis also addressed the fact that appropriate mobility models could be utilized in many important practical applications, such as in public health care units, for elderly care and monitoring, to improve the localization algorithms, in cellular communications networks to avoid traffic congestion, for designing of such systems that can predict prior users location, in economic forecasting, for public transportation systems and for developing social mobile applications.
Basically, mobility models indicate the movement patterns of users and how their position, velocity and acceleration vary with respect to time. Such models can be widely used in the investigation of advanced communication and navigation techniques. These human mobility models are normally classified into two main models, namely; entity mobility models and group mobility models. The presented work focuses on the entity mobility models.
The analysis was done in Matlab, based on the measurement data available in MDC database, the several parameters of Global Positioning System (GPS) data were extracted, such as time, latitude, longitude, altitude, speed, horizontal accuracy, horizontal Dilution of Precision (DOP), vertical accuracy, vertical DOP, speed accuracy etc. Parts of these parameters, namely the time, latitude, longitude, altitude and speed were further investigated in the context of basic random walk mobility model.
The data extracted from the measurements was compared with the 2-D random walk mobility model. The main findings of the thesis are that the random walk model is not a perfect fit for the available user measurement data, but can be used as a starting point in analyzing the user mobility models.