SocialRoute: A low-cost opportunistic routing strategy based on social contacts

Abstract

The study of social characteristics in human interactions is a fundamental topic in mobile networks. By taking advantage of this type of information, we can leverage the knowledge about the behavior of the nodes in a network, leading to better routing strategies, especially in opportunistic dissemination scenarios. The state of the art of social-based opportunistic routing algorithms applies simple social characterization metrics, such as node’s properties and communities, which cannot capture individual social links that last longer and represent stronger bonds when compared to communities. This work proposes SocialRoute, a social-based opportunistic routing algorithm that considers individual social links instead of communities to route messages efficiently. Additionally, we evaluate how deploying static relay nodes at popular locations can aid in the transmission by using dissemination profiles that can be selected based on the message content and priority. We show that SocialRoute can transmit data with a low computational cost, both in terms of obtaining the social characteristics and overhead generated during dissemination. Additionally, this approach provides a more equally distributed dissemination between the nodes, in opposition to strategies that rely heavily on individual nodes due to their popularity. Finally, we evaluate our proposed algorithm using two real mobility traces and compare it to four state-of-the-art solutions, showing that SocialRoute obtains higher delivery ratios while maintaining a fraction of the overhead.