IP Geolocation is a key enabler for the Future Internet to provide geographical location information for application services. For example, this data is used by Content Delivery Networks to assign users to mirror servers, which are close by, hence providing enhanced traffic management. It is still a challenging task to obtain precise and stable location information, whereas proper results are only achieved by the use of active latency measurements. This paper presents an advanced approach for an accurate and self-optimizing model for location determination, including identification of optimized Landmark positions, which are used for probing. Moreover, the selection of correlated data and the estimated target location requires a sophisticated strategy to identify the correct position. We present an improved approximation of network distances of usually unknown TIER infrastructures using the road network. Our concept is evaluated under real-world conditions focusing Europe.

中文翻译：

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在通往高精度 IP 地理定位的道路上：一种自我优化的模型

IP 地理定位是未来互联网为应用服务提供地理位置信息的关键推动因素。例如，内容交付网络使用此数据将用户分配到附近的镜像服务器，从而提供增强的流量管理。获得精确和稳定的位置信息仍然是一项具有挑战性的任务，而正确的结果只能通过使用主动延迟测量来实现。本文提出了一种用于位置确定的准确和自优化模型的高级方法，包括用于探测的优化地标位置的识别。此外，相关数据的选择和估计的目标位置需要复杂的策略来识别正确的位置。我们使用道路网络提出了通常未知的 TIER 基础设施的网络距离的改进近似值。我们的概念是在以欧洲为重点的现实条件下进行评估的。