An analysis of techniques for opportunistic networking
Opportunistic networks, as opposed to classic ones, rely on human-carried devices. This leads to a high mobility of all the nodes in the network and a very dynamic topology. Developing good forwarding algorithms for optimum routing in opportunistic networks presents a specific set of challenges. The most notable forwarding solutions rely on social human mobility patterns. They depend on several key factors and assumptions. The purpose of this paper is to provide an increased understanding on how these factors can influence routing performance. For this purpose we focus on the number of copies for each generated message, altruism and frequency of exchanged messages. The analysis is based on data collected from a social tracing experiment conducted at the University Politehnica of Bucharest. The setup and implementation of this experiment will also be presented in this paper.