Abstract
Delay tolerant network (DTN) known as suffering from frequent disruption, high latency and heterogeneous, resulting in low network availability. To improve DTN availability, routing protocols typically need to predict the probability of encountering the nodes. In this paper, we use the Bayesian Network (BN) to construct the knowledge base, which is an unique tool for creating a representation of the dependence relationships among DTN parameters. Then developed a Bayesian networkbased approach to estimate the contact probability among nodes of DTN. We conducted an experiment to compare our approach against its counterparts in PROPHET routing protocol and power law distribution-based method. The experiment shows our approach is superior to other methods in both recall ratio and precision in all four datasets, including HAGGLE, NUS, REALITY and SASSY.
