A delivery scheme based on fuzzy inference Routing algorithm for Human Contact Networks

Human Contact Network is a kind of DTN (Delay Tolerant Networks), and is closely related with people´ activities. Owing to its intermittent connectivity and unique human mobility patterns, how to transmit data in an effective way is a challenging problem for DTN. In this paper, considering the regularity of people activities, we propose a THM (Trip History Model) to record the activities of people. Through the spatial and temporal characteristic of people stored in THM, the further moving destination can be predicted. In order to transfer data more reasonable, Fuzzy inference Routing algorithm has been proposed, which introduce fuzzy inference into routing scheme to help select a better sensor node. Our simulation results show that, compared with LABEL and PROPHET algorithms, FIRA effectively improves the routing performance of the network.