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Lee, GM
Publisher: IEEE
Languages: English
Types: Unknown
Subjects: HA, QA75
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.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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