Enhanced Lobby Influence: Knowledge based content forwarding algorithm for opportunistic communication networks

Content transfer without any prior knowledge of the routes, always causes a challenge in opportunistic networks. Content forwarding in these networks have repercussions in the form of communication cost. Enhancement in content forwarding in opportunistic networks can be realized by targeting key nodes that show high degree of influence, popularity or knowledge inside the network. Based on these observations, this paper presents an improved version of Lobby Influence algorithm called Enhanced Lobby Influence. The forwarding decision of Enhanced Lobby Influence not only depends on the intermediate node selection criteria as defined in Lobby Influence but also based on the knowledge of previously direct content delivery of intended recipient. The experimental results have shown that the new algorithm performed extremely well against its predecessor Lobby Influence and illustrates that not only it reduces the communication cost but at the same time makes content delivery efficient for intended recipients.