An Efficient Social Network-Mobility Model for MANETs

Author(s):  
Rahul Ghosh ◽  
Aritra Das ◽  
P. Venkateswaran ◽  
S. K. Sanyal ◽  
R. Nandi
Author(s):  
Lu Yan

With recent advances of wireless ad hoc networking, especially opportunistic forwarding and cognitive radio, there is an increasing concern that existing mobility models are insufficient to represent network mobility in real world settings. In this chapter, the author discusses his proposal for a more realistic mobility model which captures key features of human movements in pervasive markets. His findings lead to a non-traditional mobility model which can be used to reconstruct the statistical patterns commonly observed in the literature, and facilitate the study of mobile communication and software engineering design problems under the context of pervasive computing for markets.


Author(s):  
Kevin Linka ◽  
Mathias Peirlinck ◽  
Francisco Sahli Costabal ◽  
Ellen Kuhl

ABSTRACTFor the first time in history, on March 17,2020, the European Union closed all its external borders to contain the spreading of the coronavirus 2019, COVID-19. Throughout two past months, governments around the world have implemented massive travel restrictions and border control to mitigate the outbreak of this global pandemic. However, the precise effects of travel restrictions on the outbreak dynamics of COVID-19 remain unknown. Here we combine a global network mobility model with a local epidemiology model to simulate and predict the outbreak dynamics and outbreak control of COVID-19 across Europe. We correlate our mobility model to passenger air travel statistics and calibrate our epidemiology model using the number of reported COVID-19 cases for each country. Our simulations show that mobility networks of air travel can predict the emerging global diffusion pattern of a pandemic at the early stages of the outbreak. Our results suggest that an unconstrained mobility would have significantly accelerated the spreading of COVID-19, especially in Central Europe, Spain, and France. Ultimately, our network epidemiology model can inform political decision making and help identify exit strategies from current travel restrictions and total lockdown.


2012 ◽  
pp. 1799-1810
Author(s):  
Lu Yan

With recent advances of wireless ad hoc networking, especially opportunistic forwarding and cognitive radio, there is an increasing concern that existing mobility models are insufficient to represent network mobility in real world settings. In this chapter, the author discusses his proposal for a more realistic mobility model which captures key features of human movements in pervasive markets. His findings lead to a non-traditional mobility model which can be used to reconstruct the statistical patterns commonly observed in the literature, and facilitate the study of mobile communication and software engineering design problems under the context of pervasive computing for markets.


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