Modeling Epidemic Data Diffusion for Wireless Mobile Networks

We propose an analytical model for data diffusion time/delay in a wireless mobile network using a novel peer-to-peer spatial-demand based information dissemination technique. The demand-based technique for data dissemination is beneficial for mobile network since this fully distributed and scalable network system utilizes only local urge for data and provides faster delivery of information. However, due to mobility and chaotic wireless network, it is difficult to predict the object diffusion time/delay among all the interested nodes in a mobile network. Therefore, the development of an analytical model to anticipate the expected time of data distribution among the nodes in a mobile system is an important area of research. In response to this problem, we first find the probabilities of transmitting object from one node to multiple nodes using the epidemic model of disease spreading. Utilizing these transition probabilities, we construct an analytical model based on Markov chain to calculate the expected delay of information diffusion. In addition, we adopt the mobility and scheduling impact on data transition probabilities in our analytical model. Extensive event-based simulations demonstrate that our analytical model provide near perfect estimation of data diffusion time/delay in wireless mobile networks.