Information Epidemics in Complex Networks with Opportunistic Links and Dynamic Topology

Wireless networks, especially mobile ad hoc networks (MANET) and cognitive radio networks (CRN), are facing two new challenges beyond traditional random network model: opportunistic links with random nature due to fading and dynamic channel access, and dynamic network topology due to mobility and time varying. For a more general networking of Internet users as social complex networks, such challenges of further importance remain open. A generic and reliable model is therefore required to capture the information dissemination dynamics (IDD) of machine- to-machine communications or interactions in relation-based social networks. Inspired from epidemiology, we investigate the IDD in well-known complex networks by modified Susceptible-Infected (SI) model, which is surprisingly suitable for above multiple scenarios. Systematically categorizing such networks and examining conditions to adopt SI model for IDD in complex networks, the fundamental properties including mixing type, vertex connectivity and giant component size provide valid insights for quantitative analysis. We also investigate the IDD in networks with time-varying topology and show that all individuals receive the information in dynamic sense, even if the giant component size is not compatible with the number of individuals in static sense. Consequently, we successfully establish such analytical model for characterizing the IDD in complex networks consisting of opportunistic links and time-varying topology, feasible for various random wireless networks and social networks.