From BGP to RTT and Beyond: Matching BGP Routing Changes and Network Delay Variations with an Eye on Traceroute Paths

Many organizations have the mission of assessing the quality of broadband access services offered by Internet Service Providers (ISPs). They deploy network probes that periodically perform network measures towards selected Internet services. By analyzing the data collected by the probes it is often possible to gain a reasonable estimate of the bandwidth made available by the ISP. However, it is much more difficult to use such data to explain who is responsible of the fluctuations of other network qualities. This is especially true for latency, that is fundamental for several nowadays network services. On the other hand, there are many publicly accessible BGP routers that collect the history of routing changes and that are good candidates to be used for understanding if latency fluctuations depend on interdomain routing. In this paper we provide a methodology that, given a probe that is located inside the network of an ISP and that executes latency measures and given a set of publicly accessible BGP routers located inside the same ISP, decides which routers are best candidates (if any) for studying the relationship between variations of network performance recorded by the probe and interdomain routing changes. We validate the methodology with experimental studies based on data gathered by the RIPE NCC, an organization that is well-known to be independent and that publishes both BGP data within the Routing Information Service (RIS) and probe measurement data within the Atlas project

Mining Network Events using Traceroute Empathy

In the never-ending quest for tools that enable an ISP to smooth troubleshooting and improve awareness of network behavior, very much effort has been devoted in the collection of data by active and passive measurement at the data plane and at the control plane level. Exploitation of collected data has been mostly focused on anomaly detection and on root-cause analysis. Our objective is somewhat in the middle. We consider traceroutes collected by a network of probes and aim at introducing a practically applicable methodology to quickly spot measurements that are related to high-impact events happened in the network. Such filtering process eases further in- depth human-based analysis, for example with visual tools which are effective only when handling a limited amount of data. We introduce the empathy relation between traceroutes as the cornerstone of our formal characterization of the traceroutes related to a network event. Based on this model, we describe an algorithm that finds traceroutes related to high-impact events in an arbitrary set of measurements. Evidence of the effectiveness of our approach is given by experimental results produced on real-world data.Comment: 8 pages, 7 figures, extended version of Discovering High-Impact Routing Events using Traceroutes, in Proc. 20th International Symposium on Computers and Communications (ISCC 2015

Exploring Flow Metrics in Dense Geographical Networks

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Dynamic visualization of service performance and routing on the internet

In this thesis we present several approaches to the problem of visualizing Internet service performance and routing data. We first consider them as two independent topics, proposing interactive tools for both. In a second phase, we introduce the possibility to correlate datasets of both types in order to obtain a combined visualization. All the proposed approaches are preceded by an informative description of the context in which the visualization is needed and the tasks that prospective users would need to perform when using the tool. Design decisions are then illustrated and motivated based on user requirements. The algorithms used for the visualization and animation of graphs and networks are described thoroughly, in particular when they clearly improve on alternatives found in the literature. Technological aspects are always mentioned and highlighted when they represent a key quality of the work. Where available, user studies and feedback collected during the development are reported and discussed. Finally, given the interactive and dynamic nature of our work, we provide the reader with support material (animations, videos, images) accessible through the Web

NetFork: Mapping Time to Space in Network Visualisation

Dynamic network visualization aims at representing the evolution of relational information in a readable, scalable, and effective way. A natural approach, called 'time-to-time mapping', consists of computing a representation of the network at each time step and animating the transition between subsequent time steps. However, recent literature recommends to represent time-related events by means of static graphic counterparts, realizing the so called 'time-to-space mapping'. This paradigm has been successfully applied to networks where nodes and edges are subject to a restricted set of events: appearances, disappearances, and attribute changes. In this paper we describe NetFork, a system that conveys the timings and the impact of path changes that occur in a routing network by suitable time-to-space metaphors, without relying on the time-to-time mapping adopted by the play-back interfaces of alternative network monitoring tools. A user study and a comparison with the state of the art show that users can leverage on high level static representations to quickly assess the quantity and quality of the path dynamics that took place in the network

How to Visualize the K-Root Name Server (Demo)

Lecture Notes in Computer Science