AbstractThis project is about epidemics spreading in computer networks and the issue of node centrality. The aim of such analysis is to investigate the rate of infection and information spreading in the network, to find the most important nodes in the network graph, and finally to answer the research question which states that ”centrality of the node has a crucial role on spreading power”.
The method used in this project to answer the research question is important because it measures the power of spreading information by one specific node and studies the environments around it, instead of environments around the whole network. So by finding the power of spreading and properties of one specific node in the network will help us understand which weaknesses or advantages this node has for maintenance or blocking hazards at the right time.
The position or location of each node in the network is studied in a form of degree, betweenness, and centrality of the node and the rate of effect those properties have on spreading of information.
Hypotheses are suggested on epidemic networks in addition to our research question and graphs are generated and analyzed, to test those hypotheses. We do so by developing a mathematical SI-model which is depending on the values of principal eigenvector to measure the number of infected nodes as a function of time, and also trying to monitor infections' movements and expressing the frequency and cumulative tables, and graphs to support and confirm our developed mathematical method.
The obtained results from our work in this thesis show that centrality of the node is related to the power of information spreading.