For a provider of a Content Delivery Network (CDN), the location selection of mirror servers is a complex optimization problem. Generally, the objective is to place the nodes centralized such that all customers have convenient access to the service according to their demands. It is an instance of the k-center problem, which is proven to be NPhard. Determining reasonable server locations directly influences run time effects and future service costs. We model, simulate, and optimize the properties of a content delivery network. Specifically, considering the server locations in a network infrastructure with prioritized customers and weighted connections. A simulation model for the servers is necessary to analyze the caching behavior in accordance to the targeted customer requests. We analyze the problem and compare different optimization strategies. For our simulation, we employ various realistic scenarios and evaluate several performance indicators. Our new optimization approach shows a significant improvement. The presented results are generally applicable to other domains with k-center problems, e.g., the placement of military bases, the planning and placement of facility locations, or data mining.

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IP Geolocation is a key enabler for many areas of application like determination of an attack origin, targeted advertisement, and Content Delivery Networks. Although IP Geolocation is an ongoing field of research for over one decade, it is still a challenging task, whereas good results are only achieved by the use of active latency measurements. Nevertheless, an increased accuracy is needed to improve service quality. This paper presents an novel approach to find optimized Landmark positions which are used for active probing. Since a reasonable Landmark selection is important for a highly accurate localization service, the goal is to find Landmarks close to the target with respect to the infrastructure and hop count. Furthermore, we introduce a new approach of an adaptable and more accurate mathematical modelling of an improved geographical location estimation process. Current techniques provide less information about solving the Landmark problem as well as are using imprecise models. We demonstrate the usability of our approach in a real-world environment and analyse Geolocation for the first time in Europe. The combination of an optimized Landmark selection and advanced modulation results in an improved accuracy of IP Geolocation.

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