Fang XuHuyin ZhangMin DengNing XuZhiyong Wang
With the growing number of smartphone users, peer-to-peer ad hoc data forwarding is expected to occur more often. The forwarding performance improves when knowledge regarding the expected topology and the social context information of the networks. In this paper, we introduce a new metric for data forwarding based on social context information, in which node's social context information is used to calculate the social similarity utility between a node and destination, and the social connection of networks is used to calculate the betweenness centrality utility of a node. We combine two utility functions to derive the social strength among users and their importance. We also present social context-based data forwarding algorithm for routing decision. Extensive simulations on real traces show that the introduced algorithm is more efficient than other state-of-art algorithms.
Jagdeep SinghSanjay Kumar DhurandherIsaac Woungang
Milena RadenkovicAndrew Grundy
Ahmad El ShoghriBranislav KusýRaja JurdakNeil Bergmann