Analytic latency model for message dissemination in opportunistic networks

Abstract

In opportunistic networks, messages are delivered based on a store-forward-carry paradigm. Network topology varies with time and dynamism of the links between nodes has a primary effect on the message delay, one of the network performance indicators. To get a precise estimation of the network latency with less complexity, a rigorous framework modeling the information propagation process is developed. The model is based on a sophisticated 2N−1-state Markov chain and yields a closed-form expression under non-homogenous assumption, as well as an asymptotic formula under homogenous assumption. Finally, to assess our model's scalability and reliability, analytical results are validated by simulations on a real-life human mobility trace and two standard mobility models. The results demonstrate that the model predicts the routing performance accurately for networks of different size and mobility models.