College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China.
Cyberspace Security Situation Awareness and Evaluation Key Laboratory of Anhui Province, Hefei 230037, China.
Sensors (Basel). 2022 Jul 28;22(15):5650. doi: 10.3390/s22155650.
In large-scale network topology discovery, due to the complex network structure and dynamic change characteristics, it is always the focus of network topology measurement to obtain as many network paths as possible in a short time. In this paper, we propose a large-scale network path probing approach in order to solve the problems of low probing efficiency and high probing redundancy commonly found in current research. By improving the packet delivery order and the update strategy of time-to-live field values, we redesigned and implemented an efficient large-scale network path probing tool. The experimental results show that the method-derived tool can complete path probing for a sample of 12 million/24 network address segments worldwide within 1 hour, which greatly improves the efficiency of network path probing. Meanwhile, compared to existing methods, the proposed method can reduce the number of packets sent by about 10% with the same number of network addresses found, which effectively reduces probing redundancy and alleviates the network load.
在大规模网络拓扑发现中，由于网络结构复杂和动态变化的特点，如何在短时间内尽可能多地获取网络路径一直是网络拓扑测量的重点。本文针对当前研究中普遍存在的探测效率低、探测冗余度高的问题，提出了一种大规模网络路径探测方法。通过改进数据包的投递顺序和生存时间字段值的更新策略，重新设计并实现了一种高效的大规模网络路径探测工具。实验结果表明，该方法设计的工具可以在 1 小时内完成对全球 1200 万个/24 个网络地址段的路径探测，大大提高了网络路径探测的效率。同时，与现有方法相比，该方法在相同数量的网络地址发现中可以减少约 10%的数据包发送量，有效地减少了探测冗余，减轻了网络负载。
