DocumentCode :
1772849
Title :
On the heavy tail properties of spatial node density for realistic mobility modeling
Author :
Ferreira, Danielle Lopes ; Nunes, Bruno A. A. ; Obraczka, Katia
Author_Institution :
Dept. of Comput. Eng., Univ. of California, Santa Cruz, Santa Cruz, CA, USA
fYear :
2014
fDate :
June 30 2014-July 3 2014
Firstpage :
504
Lastpage :
512
Abstract :
In this paper, we show empirically that the spatial node density resulting from human mobility follows a power law. We also show that the number of locales visited by users also exhibit heavy-tail behavior. We develop a stochastic model that confirms our empirical observations by showing that node mobility resulting from our model closely approximates mobility recorded in real traces collected from a variety of scenarios. Besides corroborating our empirical observations, we showcase another application of our model by using it to generate mobility regimes whose spatial node density exhibit heavy-tail behavior. We validate the resulting mobility generator by comparing its output against real traces.
Keywords :
mobile radio; stochastic processes; heavy tail properties; heavy-tail behavior; human mobility; mobility regimes; node mobility; power law; realistic mobility modeling; spatial node density; stochastic model; Analytical models; Conferences; Educational institutions; Global Positioning System; Mathematical model; Sensors; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensing, Communication, and Networking (SECON), 2014 Eleventh Annual IEEE International Conference on
Conference_Location :
Singapore
Type :
conf
DOI :
10.1109/SAHCN.2014.6990389
Filename :
6990389
Link To Document :
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