Lobby Influence: Opportunistic forwarding algorithm based on human social relationship patterns

In opportunistic networks, nodes have no prior knowledge of the routes to forward the information to its intended destination. Message transfer without generating excessive traffic poses a challenge in these networks. Improvements in message routing/forwarding in opportunistic networks can be achieved by exploiting nodes that exhibit a high level of popularity or influence within the network. Based on these observations, this paper presents a novel algorithm called Lobby Influence. The new algorithm is tested against two previously proposed algorithms and proves to be the better algorithm in terms of message delivery and delay. Moreover, unlike other social based algorithms, which have a tendency to concentrate traffic through their identified routing nodes, our algorithm provides a fairer distribution, thus alleviating the tendency to saturate individual nodes.