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This thesis investigated how performance of today's IP traffic metering and analysis applications can be improved by moving from a centralized, high-performance infrastructure, which executes these tasks, to distributed mechanisms, which combine available resources of multiple devices. The results achieved show that distributed IP traffic metering and analysis leverages bottleneck problems. The distributed IP traffic approach DITA does not solve all problems of handling such large amounts of data in very short time by itself, but proposes an orthogonal approach to existing solutions. DITA revelas that combining distributed IP traffic metering and analysis reaches better and higher performance sampling and aggregation mechanisms, which do provide a very flexible and the open solution to analyzing IP traffic in future high-speed networks. This has been achieved by the facts that all mechanisms designed for DITA - and their prototypical implementations - are based on standard protocols and open-source technologies. DITA determines the first approach to distributed IP traffic metering and analysis known today, which (a) addresses the different bottlenecks of traffic analysis in a generic way, and (b) is self-organizing, offering a scalable solution to regular traffic increases.