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See detailOn the Analysis of Internet Paths with DisNETPerf, a Distributed Paths Performance Analyzer
Wassermann, Sarah ULiege; Casas, Pedro; Donnet, Benoît ULiege et al

in Proc. 10th IEEE Workshop on Network Measurements (WNM) (2016, November)

Traceroute is the most widely used Internet path analysis tool today to study the topology of the Internet and to diagnose routing failures as well as poor performance events. A major limitation of ... [more ▼]

Traceroute is the most widely used Internet path analysis tool today to study the topology of the Internet and to diagnose routing failures as well as poor performance events. A major limitation of traceroute when the destination is not controllable by the user is its inability to measure reverse paths, i.e., the path from any given destination back to the source. This is a major drawback for ISPs, who need to understand the performance of the Internet paths connecting popular services (e.g., YouTube and Facebook) to their customers. Even if public servers and distributed measurement platforms can provide partial reverse path visibility through ad-hoc measurements, there is still a need for a structured approach capable of analyzing the performance of Internet paths connecting any pair of nodes (servers, routers, hosts, etc.). While the problem of reverse traceroute has been addressed in the past, proposed techniques rely on IP address spoofing – which might lead to security concerns, and assume the availability of certain route-tracking options –, which might not be available. In this paper, we introduce and evaluate DisNETPerf, a new tool which provides exactly the same type of information as traceroute, but for paths connecting arbitrarily selected nodes. DisNETPerf works by firstly locating probes (i.e., measurement points) that are the closest to a given target node, using them to perform traceroute measurements from the target point-of-view to a given destination for path performance monitoring and troubleshooting purposes. We propose two techniques for probe location, and demonstrate that the reverse path (from server to users) can be measured with very high accuracy in certain scenarios. We also analyze relevant characteristics of Internet paths and distributed measurement platforms, which reinforce the applicability and relevance of DisNETPerf in current Internet. [less ▲]

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See detailUnveiling Network and Service Performance Degradation in the Wild with mPlane
Casas, Pedro; Fiadino, Pierdomenico; Wassermann, Sarah ULiege et al

in IEEE Communications Magazine (2016)

Unveiling network and service performance issues in complex and highly decentralized systems such as the Internet is a major challenge. Indeed, the Internet is based on decentralization and diversity ... [more ▼]

Unveiling network and service performance issues in complex and highly decentralized systems such as the Internet is a major challenge. Indeed, the Internet is based on decentralization and diversity. However, its distributed nature leads to operational brittleness and difficulty in identifying the root causes of performance degradation. In such a context, network measurements are a fundamental pillar to shed light and to unveil design and implementation defects. To tackle this fragmentation and visibility problem, we have recently conceived mPlane, a distributed measurement platform which runs, collects and analyses traffic measurements to study the operation and functioning of the Internet. In this paper, we show the potentiality of the mPlane approach to unveil network and service degradation issues in live, operational networks, involving both fixed-line and cellular networks. In particular, we combine active and passive measurements to troubleshoot problems in end-customer Internet access connections, or to automatically detect and diagnose anomalies in Internet-scale services (e.g., YouTube) which impact a large number of end-users. [less ▲]

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See detailCross-check of Analysis Modules and Reasoner Interactions
Manferdini, U.; Traverso, S.; Mellia, Marco et al

Report (2015)

This deliverable presents an extended set of Analysis Modules, including both the improvements done to those presented in deliverable D4.1 as well as the new analysis algorithms designed and developed to ... [more ▼]

This deliverable presents an extended set of Analysis Modules, including both the improvements done to those presented in deliverable D4.1 as well as the new analysis algorithms designed and developed to address use-cases. The deliverable also describes a complete workflow description for the different use-cases, including both stream processing for real-time monitoring applications as well as batch processing for “off-line” analysis. This workflow description specifies the iterative interaction loop between WP2, WP3, T4.1, and T4.2, thereby allowing for a cross-checking of the analysis modules and the reasoner interactions. [less ▲]

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