Vehicular Social Networks (VSNs) consist of groups of individuals (i.e., people) who may share common interests, preferences and needs in the context of temporal spatial proximity on roads. In this environment, the impact of human social factors, such as mobility, willingness to cooperate and personal preferences, on vehicular connectivity is taken under consideration, thus extending the concept of Vehicular Ad-hoc Networks. In VSNs, vehicles are classified based on their social degree, a vehicle considered to be a “social” one if it accesses the vehicular social network and posts messages with a frequency higher than a given threshold. Therefore, to speed up the data dissemination process within a vehicular social network, a packet should be forwarded to those vehicles showing high social activity. In a previous paper, we introduced a new probabilistic-based broadcasting scheme called SCARF (SoCial-Aware Reliable Forwarding Technique for Vehicular Communications), and we analytically demonstrated its effectiveness in packet transmission reduction while guaranteeing network dissemination. In this paper, we assess SCARF in more realistic scenarios with real traffic traces, and we compare it with other similar techniques. We show that SCARF outperforms other approaches in terms of delivery ratio, while guaranteeing acceptable time delay values and average number of forwardings.

This paper presents the friendship and selfishness forwarding (FSF) algorithm for Delay Tolerant Networks. This novel solution is based on two social characteristics of nodes: friendship and selfishness. When a contact opportunity arises, FSF analyzes two aspects to make message forwarding decisions: first, FSF assesses the friendship strength among the pair of nodes, then it determines the individual selfishness of the relay node. Unlike other algorithms proposed in the DTN literature, we use a machine learning algorithm to quantify the friendship strength among pairs of nodes in the network. The individual selfishness of the relay node is determined by using a model based on the current level of its resources. The primary goal is to take into account the case where, despite a strong friendship with the message destination, the relay node does not accept processing the message to save its resources. By using trace-driven simulations we show that the FSF algorithm achieves better results in terms of delivery rate, average cost and efficiency.