LocalCom: A Community-based Epidemic Forwarding Scheme in Disruption-tolerant Networks

In disruption-tolerant networks (DTNs), network topology constantly changes and end-to-end paths can hardly be sustained. However, social network properties are observed in many DTNs and tend to be stable over time. To utilize the social network properties to facilitate packet forwarding, we present LocalCom, a community-based epidemic forwarding scheme that efficiently detects the community structure using limited local information and improves the forwarding efficiency based on the community structure. We define similarity metrics according to nodes' encounter history to depict the neighboring relationship between each pair of nodes. A distributed algorithm, which only utilizes local information, is then applied to detect communities and the formed communities have strong intra-community connections. We also present two schemes to first select and then prune gateways that connect communities to control redundancy and facilitate efficient inter-community packet forwarding. Extensive real-trace-driven simulation results are presented to support the effectiveness of our scheme.