An enhanced community-based mobility model for distributed mobile social networks

2012 ◽  
Vol 5 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Nikolaos Vastardis ◽  
Kun Yang
Keyword(s):  
Social Networks ◽  
Mobility Model ◽  
Mobile Social Networks ◽  
Community Based

Space-Crossing: Community-Based Data Forwarding in Mobile Social Networks Under the Hybrid Communication Architecture

2015 ◽  
Vol 14 (9) ◽  
pp. 4720-4727 ◽  
Author(s):  
Zhong Li ◽  
Cheng Wang ◽  
Siqian Yang ◽  
Changjun Jiang ◽  
Ivan Stojmenovic
Keyword(s):  
Social Networks ◽  
Mobile Social Networks ◽  
Data Forwarding ◽  
Community Based ◽  
Communication Architecture

DRL: A Multi-factor Mobility Model in Mobile Social Networks

2016 ◽  
Vol 95 (2) ◽  
pp. 1693-1711
Author(s):  
Tao Jing ◽  
Yating Zhang ◽  
Zhen Li ◽  
Yan Huo
Keyword(s):  
Social Networks ◽  
Mobility Model ◽  
Mobile Social Networks ◽  
Factor Mobility

DRL: A New Mobility Model in Mobile Social Networks

2015 ◽  
pp. 263-273
Author(s):  
Tao Jing ◽  
Yating Zhang ◽  
Zhen Li ◽  
Qinghe Gao ◽  
Yan Huo ◽  
...  
Keyword(s):  
Social Networks ◽  
Mobility Model ◽  
Mobile Social Networks

Community-based diffusion scheme using Markov chain and spectral clustering for mobile social networks

2017 ◽  
Vol 25 (2) ◽  
pp. 875-887 ◽  
Author(s):  
Jegwang Ryu ◽  
Jiho Park ◽  
Junyeop Lee ◽  
Sung-Bong Yang
Keyword(s):  
Social Networks ◽  
Markov Chain ◽  
Spectral Clustering ◽  
Mobile Social Networks ◽  
Community Based ◽  
Diffusion Scheme

scholarly journals A Study on the Node Centrality Based Multisocial Attributes Weighted in Mobile Social Networks

2018 ◽  
Vol 17 ◽  
pp. 01001
Author(s):  
Yanhong Meng ◽  
Xianxian Liu ◽  
Peirong Zhao ◽  
Yunhui Yi
Keyword(s):  
Social Networks ◽  
Social Relations ◽  
Human Mobility ◽  
Data Communication ◽  
Graph Model ◽  
Real Data ◽  
Mobility Model ◽  
Mobile Social Networks ◽  
Data Set ◽  
Binary Network

Mobile social networks (MSNs) exploit human mobility and consequent device-to-device contact to opportunistically realize data communication. Thus links in MSNs is dynamic changing over time and strongly influenced by people activities, mining influential nodes is one of the important questions for effective information transmission in MSNs. While traditional centrality definitions are based on the static binary network model and not suitable for time-varying topology structure in mobile social network. Furthermore previous centrality metrics often referred to social attributes about neighbor nodes and contact times, and did not take the contact duration time into consideration. Therefore, this paper proposes a centrality measurement method based on multi-social attributes weighted. We first use the temporal evolution graph model which more accurately depicts the dynamic nature of topology in MSNs. Quantifying human social relations and mobility model as weights for the links, and then we redefine degree of centrality and the measurement of shortest path. Finally, the superiority of the concepts we posed are evaluated in the real data set.

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