Exploiting online and offline activity-based metrics for opportunistic forwarding

Opportunistic networks are challenged wireless networks of handheld mobile devices that use contact opportunities to allow users to communicate without network infrastructure.The highly dynamic nature of these networks requires efficient forwarding mechanisms as disconnections are frequent and an end-to-end communication paradigm is not applicable. Consequently, many existing routing protocols for opportunistic networks make use of social behavior characteristics to perform hop-by-hop routing and select an appropriate relay node. Social network information is commonly extracted from encounters detected between mobile devices. However, Internet added online social interaction techniques which reflect user’s online behavior and are not based on physical meetings. In this paper we present a social-based forwarding strategy for opportunistic networks that exploits both offline and online user’s social network information. By proposing a model of dynamic online social network that uses information extracted from offline and online user behavior, we show that routing centrality metrics combining node centrality extracted from the dynamic online social network and centrality extracted from the social network detected through encounters between mobile devices are able to improve delivery ratio and even reduce the number of message replicas to be injected into the network.