高精度IP地理定位的自优化模型
On the Path to High Precise IP Geolocation: A Self-Optimizing Model
摘要：
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使能器。例如，内容分发网络使用该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。它仍然是一个具有挑战性的任务，以获得精确和稳定的位置信息，而适当的结果，只有通过使用主动延迟测量。本文提出了一种先进的方法，一个准确的和自我优化的模型，用于位置确定，包括识别优化的地标位置，这是用于探测。此外，相关数据和估计目标位置的选择需要复杂的策略来识别正确的位置。我们提出了一种改进的近似网络距离通常未知的TIER基础设施使用的道路网络。我们的概念是在现实世界的条件下评估，重点是欧洲。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
