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Failure Tolerance of Epidemic Spreading in Complex Network

Mirzasoleiman, Baharan | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 42396 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Jalili, Mahdi
  7. Abstract:
  8. Complex networks serve as generic models for many social, technological and biological systems that have been shown to share a number of common structural properties such as power-law degree distribution and small-worldness. These networks determine interactions and influence the spread of diseases, behaviours and ideas. Epidemics and failures like new behaviours ideas and innovations can spread throughout a network and prevent it from doing its functionalities. In this work, we investigate error and attack tolerance of epidemic spreading in complex networks. The main content of this thesis is arranged in three sections as follows: Firstly, the effect of random and systematic failures is investigated in biological networks. Real-world networks are composed of building blocks called motifs that are indeed specific subgraphs of (usually) small number of nodes. Network motifs are important in the functionality of complex networks. In this section we investigated how random and systematic failures in the edges of biological networks influenced their motif structure.We showed that although biological networks have been shown to be robust against random failures in terms of network connectedness and efficiency, such failures can have destructive effects on network motifs. Furthermore, the tolerance of cascaded failures was investigated in weighted networks. Many technological networks might experience random and/or systematic failures in their components. More destructive situation can happen if the components have limited capacity, which the failure in one of them might lead to a cascade of failures in other components, and consequently break down the structure of the network. In this section, we investigated the tolerance of cascaded failures in weighted networks. Three weighting strategies were considered including the betweenness centrality of the edges, the product of the degrees of the end nodes, and the product of their betweenness centralities. Then, the effect of the cascaded attack was investigated by considering the local weighted flow redistribution rule. We found that the networks in which the weight of each edge is the multiplication of the betweenness centrality of the end nodes had the best robustness against cascaded failures. In other words, the case where the load of the links is considered to be the product of the betweenness centrality of the end nodes is favored for the robustness of the network against cascaded failures. Finally, we studied epidemic spreading on scale-free networks assuming a limited budget for immunization. Since an individual cannot become infected through its immunized neighbors, we proposed a general model in which the immunity of an individual against the disease depends on the set of its immunized friends in the network. Furthermore, we considered the possibility that each individual might be eager to pay a price to buy the vaccine and become immune against the disease. These values can be added to the initial budget in order to increase the global immunity in the network. We introduced two approaches for finding appropriate offer sequence. Extensive computational experiments on artificially constructed model networks as well as a number of real-world networks revealed that these strategies can extensively increase the global immunity-per-budget in scale-free networks
  9. Keywords:
  10. Complex Network ; Error ; Fault Tolerance ; Failure Analysis ; Epidemic Spreading ; Attack Tolerance ; Immunization

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