A Method for Group Mobility Model Construction and Model Representation from Positioning Data Set Using GPGPU


KIPS Transactions on Software and Data Engineering, Vol. 6, No. 3, pp. 141-148, Mar. 2017
10.3745/KTSDE.2017.6.3.141,   PDF Download:
Keywords: Group Mobility Model, Clustering, Parallel Computing
Abstract

The current advancement of mobile devices enables users to collect a sequence of user positions by use of the positioning technology and thus the related research regarding positioning or location information are quite arising. An individual mobility model based on positioning data and time data are already established while group mobility model is not done yet. In this research, group mobility model, an extension of individual mobility model, and the process of establishment of group mobility model will be studied. Based on the previous research of group mobility model from two individual mobility model, a group mobility model with more than two individual model has been established and the transition pattern of the model is represented by Markov chain. In consideration of real application, the computing time to establish group mobility mode from huge positioning data has been drastically improved by use of GPGPU comparing to the use of traditional multicore systems.


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Cite this article
[IEEE Style]
S. H. Yoon and K. D. Yup, "A Method for Group Mobility Model Construction and Model Representation from Positioning Data Set Using GPGPU," KIPS Transactions on Software and Data Engineering, vol. 6, no. 3, pp. 141-148, 2017. DOI: 10.3745/KTSDE.2017.6.3.141.

[ACM Style]
Song Ha Yoon and Kim Dong Yup. 2017. A Method for Group Mobility Model Construction and Model Representation from Positioning Data Set Using GPGPU. KIPS Transactions on Software and Data Engineering, 6, 3, (2017), 141-148. DOI: 10.3745/KTSDE.2017.6.3.141.