Spreading Process On Complex Network

Network science is an academic research area which offers a unique point of view to tackle complex problems in many fields such as computer networks,social networks,biologicalnetworks,etc.The network science pays much more attention to the interactions between different parts of complex systems more than individual themselves.There are some fundamental aspects which are covered in the study of network science including network structures and the network dynamical process models and how they interact with each other.We are more interested to examine complex problems in the field of network science such as the random walk or random spreading process,transportation network,and traffic dynamics.In this dissertation,we present the spreading process on complex networks with different perspectives.First,we discuss predator capture problem,which is a prototype in many network related applications.In this research work,we study the capture process on complex network by considering multiple predators from multiple sources.Initially,some lions start from multiple sources at the same time to capture the lamb by biased random walk.We derive the equations of life-time and expected life time of lamb.It shows that expected life-time drops substantially with the increasing number of lions.We also study that topological structure affects the capture process,and realized that locating on small degree node is better than large degree node to prolong the life-time of the lamb.Next,we study the life-time and traffic congestion on dynamical networks with limited power supply.We derive the network lifetime based on the level of traffic congestion.We also study that how the factors such as packet generation rate,communication radius,node speed,etc.affect the network lifetime and traffic congestion as well.In the end,we study the epidemic spreading process driven by biased random walks,and focus on the size of infected population and the size of the ever infected population.Our simulation and analytical results shows that the epidemic spreading becomes intense and wide with the increase the delivery capacity of infected,average node degree,and the homogeneity of node degree distribution.Furthermore,the optimal parameter such that the infected nodes have the largest population and the epidemic spreading process covers the largest part of the network.