uncertainty-aware reputation system in mobile networks

Many emerging mobile networks aim to provide wireless network services without relying on any infrastructure. The main challenge in these networks comes from their self-organized and distributed nature. There is an inherent reliance on collaboration among the participants in order to achieve the aimed functionalities. Therefore, establishing and quantifying trust, which is the driving force for collaboration, is important for applications in mobile networks. This dissertation focuses on evaluating and quantifying trust to stimulate collaboration in mobile networks, introducing uncertainty concepts and metrics, as well as providing the various analysis and applications of uncertainty-aware reputation systems. Many existing reputation systems sharply divide the trust value into right or wrong, thus ignoring another core dimension of trust: uncertainty. As uncertainty deeply impacts a node's anticipation of others' behavior and decisions during interaction, we include it in the reputation system. Specifically, we use an uncertainty metric to directly reflect a node's confidence in the sufficiency of its past experience, and study how the collection of trust information may affect uncertainty in nodes' opinions. Higher uncertainty leads to higher transaction cost and reduced acceptance of communication. We exploit mobility to efficiently reduce uncertainty and to speed up trust convergence. We also apply the new reputation system to enhance the analysis of the interactions among mobile nodes, and present three sample uncertainty-aware applications. We integrate the uncertainty-aware reputation model with game theory tools, and enhance the analysis on interactions among mobile nodes.