  In opportunistic networks, the use of social metrics (e.g., degree, closeness
and betweenness centrality) of human mobility network, has recently been shown
to be an effective solution to improve the performance of opportunistic
forwarding algorithms. Most of the current social-based forwarding schemes
exploit some globally defined node centrality, resulting in a bias towards the
most popular nodes. However, these nodes may not be appropriate relay
candidates for some target nodes, because they may have low importance relative
to these subsets of target nodes. In this paper, to improve the opportunistic
forwarding efficiency, we exploit the relative importance (called partial
centrality) of a node with respect to a group of nodes. We design a new
opportunistic forwarding scheme, opportunistic forwarding with partial
centrality (OFPC), and theoretically quantify the influence of the partial
centrality on the data forwarding performance using graph spectrum. By applying
our scheme on three real opportunistic networking scenarios, our extensive
evaluations show that our scheme achieves significantly better mean delivery
delay and cost compared to the state-of-the-art works, while achieving delivery
ratios sufficiently close to those by Epidemic under different TTL
requirements.
