Lee, GM (2016) Understanding the Impact of Network Structure on Propagation Dynamics based on Mobile Big Data. In: Wireless Communications and Mobile Computing Conference (IWCMC) . (International Wireless Communications & Mobile Computing Conference, 05 September 2016 - 09 September 2016, Paphos, Cyprus).

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Abstract

Understanding the propagation dynamics of information and epidemic on complex networks is very important for discovering and controlling a terrorist attack, and even for predicting a disease outbreak. How to track, recognize and model such dynamics is a big challenge. Along with the popularity of smart devices and the rapid development of Internet of Things (IoT), massive mobile data is automatically collected. In this article, as a typical use case, we investigate the impact of network structure on epidemic propagation dynamics by analyzing the mobile data collected from smart devices carried by the volunteers of Ebola outbreak areas. From this investigation, we obtain two observations. Based on these observations and the analytical ability of Apache Spark on Streaming Data and Graph, we propose a simple model to recognize the dynamic structure of a network. Moreover, we introduce and discuss open issues and future work for developing the proposed recognition model.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science & Mathematics
Publisher:	IEEE
Date Deposited:	06 May 2016 11:33
Last Modified:	13 Apr 2022 15:14
URI:	https://researchonline.ljmu.ac.uk/id/eprint/3576

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