Opportunistic Forwarding based on the weighted social characteristics in MSNs

Exploiting social characteristics to make opportunistic forwarding decisions in mobile social networks offers a new approach to improve the forwarding performance and reduce the additional network workload. Actually, people in social networks will have more opportunities to contact with each other if they have more similar characteristics. In this paper, the data forwarding strategy is investigated through the weighted Characteristic-based Opportunistic Forwarding (COF) scheme, in which the weight for each characteristic is computed by exploring the contact frequency of the nodes. In our approach, the message is forwarded to the node which has more common characteristics with the destination. Furthermore, we compare the proposed COF scheme with several benchmark forwarding algorithms, including PeopleRank, Spray&Wait, Epidemic and Wait destination. The validity of the modeling and the accuracy of the analysis are verified through the extensive simulations with real traces, which also guide the design of more sophisticated data forwarding schemes.