Impact of mobility models on social structure formation in opportunistic networks
In mobile opportunistic networks, the network topology is unpredictable and very dynamic due to the existence of the mobile nodes in the network. The nodes’ mobility affect the nodes’ interaction frequency. Hence, it also affecting the social structure formation between nodes. In this paper, we stu...
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2013
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my.unimas.ir.157652017-05-02T00:59:20Z http://ir.unimas.my/id/eprint/15765/ Impact of mobility models on social structure formation in opportunistic networks Halikul, Lenando Mohamad Nazim, Jambli Kartinah, Zen Johari, Abdullah T Technology (General) In mobile opportunistic networks, the network topology is unpredictable and very dynamic due to the existence of the mobile nodes in the network. The nodes’ mobility affect the nodes’ interaction frequency. Hence, it also affecting the social structure formation between nodes. In this paper, we study the impact of different mobility models namely Random Walk, Random Waypoint, Gauss Markov and D-GM on the social structure formation in opportunistic networks. The study shows that different mobility models have different impact on the social structures formation. Based on our experimental results, the Gauss Markov model provides better social structure compared to others because it creates more opportunities for a node to interact with different nodes. 2013 Conference or Workshop Item PeerReviewed text en http://ir.unimas.my/id/eprint/15765/1/Impact%20of%20mobility%20models%20on%20social%20structure%20formation%20in%20opportunistic%20networks%20%28abstrak%29.pdf Halikul, Lenando and Mohamad Nazim, Jambli and Kartinah, Zen and Johari, Abdullah (2013) Impact of mobility models on social structure formation in opportunistic networks. In: 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications,, 16 July 2013 through 18 July 2013;, TrustCom 2013; Melbourne, VIC; Australia;. DOI: 10.1109/TrustCom.2013.270 |
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T Technology (General) |
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T Technology (General) Halikul, Lenando Mohamad Nazim, Jambli Kartinah, Zen Johari, Abdullah Impact of mobility models on social structure formation in opportunistic networks |
| description |
In mobile opportunistic networks, the network topology is unpredictable and very dynamic due to the existence
of the mobile nodes in the network. The nodes’ mobility affect the nodes’ interaction frequency. Hence, it also affecting the social structure formation between nodes. In this paper, we study the impact of different mobility models namely Random Walk, Random Waypoint, Gauss Markov and D-GM on the social structure formation in opportunistic networks. The study shows that different mobility models have different impact on the social
structures formation. Based on our experimental results, the Gauss Markov model provides better social structure compared to others because it creates more opportunities for a node to interact with different nodes. |
| format |
Conference or Workshop Item |
| author |
Halikul, Lenando Mohamad Nazim, Jambli Kartinah, Zen Johari, Abdullah |
| author_facet |
Halikul, Lenando Mohamad Nazim, Jambli Kartinah, Zen Johari, Abdullah |
| author_sort |
Halikul, Lenando |
| title |
Impact of mobility models on social structure formation in opportunistic networks |
| title_short |
Impact of mobility models on social structure formation in opportunistic networks |
| title_full |
Impact of mobility models on social structure formation in opportunistic networks |
| title_fullStr |
Impact of mobility models on social structure formation in opportunistic networks |
| title_full_unstemmed |
Impact of mobility models on social structure formation in opportunistic networks |
| title_sort |
impact of mobility models on social structure formation in opportunistic networks |
| publishDate |
2013 |
| url |
http://ir.unimas.my/id/eprint/15765/1/Impact%20of%20mobility%20models%20on%20social%20structure%20formation%20in%20opportunistic%20networks%20%28abstrak%29.pdf http://ir.unimas.my/id/eprint/15765/ |
| _version_ |
1644512226542878720 |
| score |
13.250461 |