A Scalable Architecture for Monitoring and Visualizing Multicast Statistics

An understanding of certain network functions is critical for successful network management. Managers must have insight into network topology, protocol performance and fault detection/isolation. The ability to obtain such insight is even more critical when trying to support evolving technologies like multicast. With these technologies, the pace of change is high, modi cations to routing mechanisms are frequent, and faults are common. In this paper we introduce Mantra, a tool we have developed to monitor multicast. Mantra collects, analyzes, and visualizes network-layer (routing and topology) data about the global multicast infrastructure. The two most important functions of Mantra are: (1) monitoring multicast networks on a global scale; and (2) presenting results in the form of intuitive visualizations. To achieve accurate monitoring, Mantra collects data from several topologically and geographically diverse networks. For the purpose of presentation, Mantra uses several interactive visualization mechanisms to present statistics, topology maps and geographic properties. Another noteworthy feature of Mantra is its exible and scalable architecture. This architecture helps keep our monitoring e orts current with the fast pace of multicast developments. It also enables us to expand Mantra's monitoring scope to more networks and larger data sets.