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Diffusion in Networks: Source Localization, History Reconstruction and Real-Time Network Robustification

Abstract Diffusion processes in networks can be used to model many real-world processes, such as the propagation of a rumor on social networks and cascading failures on power networks. Analysis of diffusion processes in networks can help us answer important questions such as the role and the importance of each node in the network for spreading the diffusion and how to top or contain a cascading failure in the network. This dissertation consists of three parts.

In the first part, we study the problem of locating multiple diffusion sources in networks under the Susceptible-Infected-Recovered (SIR) model. Given a complete snapshot of the network, we developed a sample-path-based algorithm, named clustering and localization, and proved that for regular... (more)
Created Date 2018
Contributor Chen, Zhen (Author) / Ying, Lei (Advisor) / Tong, Hanghang (Advisor) / Zhang, Junshan (Committee member) / He, Jingrui (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Computer science / Computer engineering / information diffusion / robustness / rumor source / social networks
Type Doctoral Dissertation
Extent 163 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Electrical Engineering 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis