Social-aware Opportunistic Routing: The New Trend

Abstract

Since users move around based on social relationships and interests, the resulting movement patterns can represent how nodes are socially connected (i.e., nodes with strong social ties, nodes that meet occasionally by sharing the same working environment). This means that social interactions reflect personal relationships (e.g., family, friends, co-workers, passers-by) that may be translated into statistical contact opportunities within and between social groups over time. Such contact opportunities may be exploited to ensure good data dissemination and retrieval, even in the presence of intermittent connectivity. Thus, in the last years, a new trend based on social similarity emerged where social relationships, interests, popularity and among others, are used to improve opportunistic routing. In this chapter, the reader will learn about the different approaches related to opportunistic routing focusing on the social-aware approaches and how such approaches make use of social information derived from opportunistic contacts to improve data forwarding. Additionally, a brief overview on the existing taxonomies for opportunistic routing as well as an updated one are provided along with a set of experiments in scenarios based on synthetic mobility models and human traces in order to show the potential of social-aware solutions.