Due to the persistent growth of the Internet’s size and performance demand it becomes more and more important to develop monitoring measurements that can narowly investigate it’s construction and operation. This degree thesis focuses on specific analyses of data paths in order to discover relevant alterations and to collect useful statistical data. The data paths that I analyze come from the measurement outcomes of a global computer network.
The analyses are made at the Internet’s autonome systems’s (AS) level. Those cases are detected in which different data paths evolve at different times between given Internet nodes at AS level. It is also explored when new connections between AS-es evolve. Quality analyses are made of AS-es according to their direct relations and inner routes. Statistical sequences can be set of the AS-es that have the most stabile connections, according to the number of different data connections that exsist between them. On the basis of the analysis results for example the flexibility of AS choices can be measured depending on which nearby AS they have forwarded the data in order to reach the given destination.
All in all, the results provide information about the construction and dynamics of the AS level of the Internet.