Epidemic Content Distribution in Mobile Networks : A study of epidemic content distribution characteristic with social relationship evaluation

Abstract: With the growing popularity of integrating mobile networks and social networks, people now enjoy a freer and more efficient means of communication. Smarter mobile devices facilitate modern human life. In the information age, various new types of information have begun to appear. How to disseminate content to people in a swift and fair way has long been a question. Choosing the right strategy for content distribution is especially crucial for mobile social networks. In this thesis project we use epidemic models for content distribution in mobile social networks. Stochastic mobility models and an SIR epidemic model are set up in the evaluation. We analyze the impact of various parameters of mobility models and epidemic model on content distribution’s success rate and delivery delay. Also, we exploit the social relationships to facilitate content distribution and show the impact of social relationships on content distribution. Simulations have shown that increasing speed and node number in the mobility models will have positive impact on content distribution success rate as well as decreasing the delay. The infect time limit and infect count limit of the epidemic model are also important for swiftly distributing content while considering energy consumption and fairness for nodes. In the social relationship simulation, nodes’ meeting times during a period of time are calculated and a threshold based on a certain level of meeting times is used for categorizing the friendship relationships between nodes. The results show that it will be easier for a successful distribution to be achieved as the social relationship between nodes gets stronger. Also, the delay shows a decreasing trend until reaching the ideal distribution delay time.