# A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach
## 2 Literature Review
Delivery Probability Routing (DPR) [23] is an enhanced SnW router supported by a delivery probability mechanism. The latter consists of implementing a probability vector which regroups the network contacts. DPR updates this vector in both spray phase and wait phase where every node exchanges its probability vector with its contacts. This approach serves optimizing the spray phase by adjusting the remaining quota of the number of each bundle copies. Consequently, the wait phase is triggered separately for each bundle depending on the quality of the available contacts' delivery probability values. As a result, the bundles having relay nodes with higher delivery probability get quicker to the wait phase. HOMME-ProPHET [24] is another variety of ProPHET which includes the meeting historic of previous hops to the delivery predictability of known nodes in order to improve the routing decision of SCF node selection. Thus, the calculation of delivery predictability of each candidate SCF node considers the previous bundles' passed nodes. Each bundle stores a probabilistic metric which estimates its delivery predictability based on its hop count and the historic of passed hops. This approach helps to take the forwarding decision by differentiating between bundles considering the quality of passed path until the host node and quality of the available delivery predictability values. Schedule-ProPHET [25] is another probabilistic DTN router for Internet-of-Things (IoT) conceived to enhance the transmission and storage capacities of ProPHET by introducing two buffer scheduling mechanisms on the basis of delivery predictability. The latter orientates the priority of bundles in the buffer cache for either forwarding or deleting decisions. The first mechanism is the bundle management which defines the dropping priority for bundles in the case of full buffer cache. The second mechanism is the bundle transfer which includes the bundle transfer to the last destination, delivery predictability, information exchange and path selection. The latter regards the traffic load and hop count as tiebreaker to the paths having tied accumulated delivery predictability values. Social Grouping-Based Routing (SGBR) [26] is a social-based DTN router extracted from the grouping behavior of taxi vehicles following their trajectories. SGBR considers the meeting frequency between nodes to approximate the connectivity predictability between each node and a group of nodes increasingly. The purpose is to limit the multiple-copy forwarding of bundle copies to such groups so that the ratio of overheads is reduced. On the other hand, the single-copy forwarding is performed within grouped nodes. Increasingly, the meeting historic between every pair of nodes is built in order to update the node's connectivity degree which is the major parameter of nodes grouping. The connectivity degree is limited by a predefined threshold for acting the decision between forwarding or dropping bundles. AntProPHET [27] is an ACO-inspired ProPHET-based router inspired from the food foraging of the swarm of ants. AntProPHET reduces the probabilistic selection of the next-SCF node to the process of food nest tracking by ants to enhance the bundles' delivery probability regarding reducing the ratio of generated overheads. Thus, the PRoPHET's predictability calculation is updated following the pheromone concentration decay formulae in Equation (2) where the nodes offering higher pheromone values are more likely to be selected as bundles' carrier node. \[\tau_{ij}=(1-\varphi).\tau_{ij}+\varphi.\tau_{0} \tag{2}\]  
\(\varphi\) is the pheromone decay coefficient and \(\tau_{0}\) the initial pheromone value.