The dissemination speed of correlated messages in opportunistic networks

We evaluate the performance of epidemic protocol in opportunistic networks. Early works follow an independent model which assumes that different messages in the network disseminate independently. Whereas, most recent work has pointed out that the same event can be detected by multiple nodes at different locations or different moments. Hence, the messages sensed by different nodes, indicating the same event, have spatial-temporal correlations. It is necessary to build an accurate mathematical model for reflecting the message dissemination process of epidemic protocol for further designing or optimizing the family of flooding protocols. However, the independent model does not provide good performance estimates in this situation. In this paper, we try to solve the problem by using a correlated model which takes into account the correlations among messages and permits the different messages denoting the same event to be aggregated in their propagation processes, and the numerical results show a close match with our theoretical analysis. Compared to the previous work, our correlated model, on the one hand, allows a network engineer to implement such a system with optimized performance confidently in an intermittently connected environment, on the other hand, our work offers a fresh insight into the spatial-temporal correlations of the messages and achieves good performance metrics in scalability.