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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, the authors 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. They define similarity metrics according to nodes' encounter history to depict the neighboring relationship between each pair of nodes.
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