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City-level geolocation algorithm of network entities based on landmark clustering

机译:基于地标聚类的网络实体城市级地理定位算法

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For the existing network entity geolocation algorithms based on the delay measurement are usually suffer from the inflation and jitter of the network delay, a new algorithm of city-level geolocation based on landmark clustering is proposed in this paper. According to the feature of the delays tend to be similar among the neighboring network entities generally, city-level network entities geolocation algorithm based on landmark clustering is given. In the proposed algorithm, the city-level landmarks are divided into several clusters based on the "delay similarity" principle to filters out the high-reliability landmarks for improving the precision of city-level geolocation algorithm, the minimal relative delay between cluster and target is calculated based on the minimal relative delay, and the region of this cluster is taken as the estimation of target's location. The rationality of the delay clustering, feasibility of the proposed algorithm, and experimental results show that the proposed algorithm reduces effectively the delay influence on the IP geolocation algorithms, and the geolocation accuracy is higher than the classic GeoPing algorithm.
机译:针对现有的基于时延测量的网络实体地理定位算法通常遭受网络延迟的膨胀和抖动的影响,提出了一种新的基于地标聚类的城市级地理定位算法。根据时延的特点,通常在相邻网络实体之间存在相似性,提出了基于地标聚类的城市级网络实体地理定位算法。在该算法中,基于“时延相似度”原理将城市地标划分为多个聚类,以过滤出高可靠性的地标,以提高城市级地理定位算法的精度,聚类与目标之间的最小相对时延。基于最小相对延迟来计算,然后将该聚类的区域作为目标位置的估计。时延聚类的合理性,所提算法的可行性以及实验结果表明,所提算法有效地降低了时延对IP地理位置算法的影响,并且地理位置精度高于经典的GeoPing算法。

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