PeopleRank: Social Opportunistic Forwarding

12 years 4 months ago
PeopleRank: Social Opportunistic Forwarding
— In opportunistic networks, end-to-end paths between two communicating nodes are rarely available. In such situations, the nodes might still copy and forward messages to nodes that are more likely to meet the destination. The question is which forwarding algorithm offers the best trade off between cost (number of message replicas) and rate of successful message delivery. We address this challenge by developing the PeopleRank approach in which nodes are ranked using a tunable weighted social information. Similar to the PageRank idea, PeopleRank gives higher weight to nodes if they are socially connected to other important nodes of the network. We develop centralized and distributed variants for the computation of PeopleRank. We present an evaluation using real mobility traces of nodes and their social interactions to show that PeopleRank manages to deliver messages with near optimal success rate (i.e., close to Epidemic Routing) while reducing the number of message retransmissions by...
Abderrahmen Mtibaa, Martin May, Christophe Diot, M
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Authors Abderrahmen Mtibaa, Martin May, Christophe Diot, Mostafa H. Ammar
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