RIM: Relative-importance based data forwarding in people-centric networks

The fast penetration of mobile phones has arisen the requirement to share content (e.g., news, photo, music, video clips, etc.) among devices. To improve the efficiency of content sharing, recent works select nodes with high centrality in the system to cache and forward contents, resulting in a bias towards the most popular nodes. However, these nodes are not the appropriate candidates for target nodes, since the globally powerful nodes may have little influence on some local communities where the targets belong. Interestingly, we observe that nodes with low global centrality but high relative importance to the targets bear most weight on content allocation. Motivated by this observation, we exploit the relative importance of a node with respect to a group of nodes to guide the allocation process. We quantify the relative importance of nodes using graph spectrum theory, we then propose RIM (Relative IMportance), a novel data forwarding scheme to improve the allocation efficiency. By applying RIM on three real people-centric scenarios, the evaluation results show that RIM achieves significantly better mean delivery delay and cost than the state-of-the-art solutions, while achieving delivery ratios sufficiently close to those by Epidemic under different message TTL requirements.