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A Multilayer Approach to Network Immunization Based on Digital Information

Joneydi, Sara | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 48390 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Khansari, Mohammad
  7. Abstract:
  8. Researching in the field of optimization of network immunizing and epidemic spreading is an active and important area. According to literature review, influential nodes are detected based on global graph metrics such as centrality measures. On the other hand, when a network infrastructure is not available and a direct or straight path between source and destination may not be accessible, one can use opportunistic networks routing protocols in Delay Tolerant Networks to recognize influential users is an appropriate approach. In this work, we use a real world three layer dataset which consists of digital data (social relations and Bluetooth contact traces) of individuals. We convert the real world transactions to a multilayer network by using Delay Tolerant Network. Then we employed link prediction method to preprocess the topology of layers (contact traces and interests layers).The influential nodes obtained from previous phase is used as an input to find most central nodes based on five important centrality measures in order to use targeted immunizing our multi-layer mobile social network under SIR (Susceptible-Infected-Removed) epidemic model. Experimental results show importance of using contact duration in immunization process compared with method which uses number of contacts. Considering two important immunization parameters (largest connected component and epidemic threshold), the proposed method shows progressive immunization in comparison with the other method
  9. Keywords:
  10. Immunization ; Digital Data ; Delay Tolerant Networks (DTN) ; Epidemic Models ; Multilayer Network ; Social Relations ; Contact Traces

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