大规模IPv6骨干网拓扑发现研究与实现

Research and realization on large scale IPv6 backbone network topology discovery

针对目前在大规模IPv6骨干网拓扑发现中普遍存在效率低、无法保证覆盖率的问题,提出一种基于ICMPv6(Internet controlmessages protocol version 6)的自学习选取探测目标点的网络拓扑发现方案,并采用IPv6Source Routing机制解决网络拓扑发现中存在的cross-link问题和路由器多址问题,最后通过对全球IPv6骨干网和国内CERNET2骨干网拓扑发现证明,该方案在保证高覆盖率的前提下,大大提高了拓扑发现效率。

In view of the fact that there always exist problems in the present large scale discovery of IPv6 backbone network topology such as low efficiency and short of coverage rate, this paper brought forward a network topology discovery scheme on choosing the probing target by self-learning, which was based on ICMPv6. By virtue of IPv6 source routing mechanism, also solved cross-link problem and the multiple access router problem both of which often exist in the present topology discovery. Finally, it was proved through the experiment on the topology discovery for the IPv6 backbone network around the world and the national backbone network that the scheme presented largely enhances the discovery efficiency while also ensuring a high coverage rate at the same time.