Spraying the replication probability with geographic assistance for Delay Tolerant Networks

Receiving great interest from the research community, Delay Tolerant Networks (DTNs) are a type of Next Generation Networks (NGNs) proposed to bridge communication in challenged environments. In this paper, the message replication probability is proportionally sprayed for efficient routing mainly under sparse scenario. This methodology is different from the spray based algorithms using message copy tickets to control replication. Our heuristic algorithm aims to overcome the scalability of the spray based algorithms, since to determine the initial value of the copy tickets requires the assumption that either the number of nodes is known in advance, or the underlying mobility model follows the Random WayPoint (RWP) characteristic. Specifically, in combining with the assistance of geographic information to estimate the movement range of destination, the routing decision is based on the encounter angle between pairwise nodes, and is dynamically switched between the designed two routing phases, named as geographic replication and replication probability spray. Furthermore, messages are under prioritized transmission with the consideration of redundancy pruning. Simulation results show our heuristic algorithm outperforms other well known algorithms in terms of delivery ratio, transmission overhead, average latency as well as buffer occupancy time.