History and grouping based probabilistic routing in DTNs

Delay and Tolerant Networks (DTNs) have been proposed to address data communication challenges in network scenarios, where no instantaneous end-to-end path is guaranteed because of frequent and long duration network partitions. Typical protocols forward a message to multiple nodes to improve message delivery rate. However, a large number of replications of original messages consume a large amount of system resources that are quite limited in such scenarios. History and Grouping based Probabilistic Routing (HGPR) is proposed in this paper to reduce the number of replications by limiting the range of message "infection" of Epidemic. Nodes are divided into different groups, and the "epidemic" only happens within certain groups. History contacts information is used for group selecting in HGPR. Simulation results show that HGPR performs better than both Epidemic and PROPHET in the community scenario, and it outperforms G-Epidemic in some metrics.