<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>We adopt temporal graph model to explore the dynamic temporal properties of three mobility datasets in DTN (Delay Tolerant Network), collected from different sources, including one university campus WLAN and two conferences WLANs. With this model, we observe that the temporal network density of DTN changes with time and approximate varies periodically. Then we study the impact of this phenomenon on information diffusion. Our studies and findings can be used for establishing more realistic mobile model, building intelligent routing algorithm, and design advanced applications for DTNs.</p>
</abstract>

We adopt temporal graph model to explore the dynamic temporal properties of three mobility datasets in DTN (Delay Tolerant Network), collected from different sources, including one university campus WLAN and two conferences WLANs. With this model, we observe that the temporal network density of DTN changes with time and approximate varies periodically. Then we study the impact of this phenomenon on information diffusion. Our studies and findings can be used for establishing more realistic mobile model, building intelligent routing algorithm, and design advanced applications for DTNs.

Cyclic Temporal Network Density and its impact on Information Diffusion for Delay Tolerant Networks

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

We adopt temporal graph model to explore the dynamic temporal properties of three mobility datasets in DTN (Delay Tolerant Network), collected from different...

Cyclic Temporal Network Density and its impact on Information Diffusion for Delay Tolerant Networks

Publié en ligne: 12 déc. 2017

Pages: 35 - 52

Reçu: 15 oct. 2010

Accepté: 09 févr. 2011

DOI: https://doi.org/10.21307/ijssis-2017-425

© 2011 Lintao Yang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.