Péter Mátray

Spotter: A model based active geolocation service

The localization of Internet hosts opens space for a wide scope of applications, from targeted, location aware content provision to localizing illegal content. In this paper we present a novel probabilistic approach, called Spotter, for estimating the geographic position of Internet devices with remarkable precision. While the existing methods use landmark specific calibration for building their internal models we show that the delay-distance data follow a generic distribution for each landmark. Hence, instead of describing the delay-distance space in a landmark specific manner our proposed method handles all the calibration points together and derives a common delay-distance model. This fundamental discovery indicates that, in contrast to prior techniques, Spotter is less prone to measurement errors and other anomalies such as indirect routing. To demonstrate the robustness and the accuracy of Spotter we test the performance on PlanetLab nodes as well as on a more realistic reference set collected by CAIDA explicitly for geolocation comparison purposes. To the best of our knowledge, we are the first to use this novel ground truth containing over 23000 network routers with their geographic locations.

A detailed path-latency model for router geolocation

This study outlines two novel techniques which can be used in the area of IP geolocation. First we introduce a detailed path-latency model to be able to determine the overall propagation delays along the network paths more accurately. This knowledge then leads to more precise geographic distance estimation between network routers and measurement nodes. In addition to the application of the detailed path-latency model, we describe a method which utilizes high-precision one-way delay measurements to further increase the accuracy of router geolocation techniques. The precise one-way delay values are used as a “path-constraint” to limit the overall geographic distance between the measurement nodes. The approach introduced in this paper can be used to localize all the network routers along the network path between the measurement nodes and can be combined with other existing geolocation techniques. The introduced techniques are validated in a wide range of experiments performed in the ETOMIC measurement infrastructure.

On the network geography of the Internet

The geographic layout of the physical Internet inherently determines important network properties and traffic characteristics. To give insight into the geography of the Internet, we examine the spatial properties of the topology and routing. To represent the network we conducted a geographically dispersed traceroute campaign, and embedded the extracted topology into the geographic space by applying a novel IP geolocalization service, called Spotter. In this paper we present the frequency analysis of link lengths, quantify path circuitousness and explore the symmetry of end-to-end Internet routes.

Results of Large-Scale Queueing Delay Tomography Performed in the ETOMIC Infrastructure

This paper presents operational experience of large-scale unicast network tomography, that samples a part of the European Internet. In the paper we describe in detail the ETOMIC measurement platform that was used to conduct the experiments, and its potential in future scaled-up measurements. The main results of the paper are maps showing various spatial and temporal structure in the characteristics of queueing delay corresponding to the resolved part of the European Internet. These maps reveal that the average queueing delay on different network segments spans more than two orders of magnitude. At the most loaded time of day we find that the distribution of average queueing delays among the different segments follows closely a log-normal distribution.

Challenges of an information model for federating virtualized infrastructures

Users of the Future Internet will expect seamless and secure access to virtual resources distributed across multiple domains. These federated platforms are the core of the Future Internet. It is clear that information models, and concrete implementation in data models, are necessary prerequisites for all federative operations, information exchanges, and service support. This position paper describes our approach to the development of an information model for federating virtual infrastructures. Our basic assumption is that semantic resource descriptions with context-awareness, in the form of Semantic Web descriptions, better support services in federated platforms. We use our experiences in the development of two ontologies for computer networks and for network monitoring, NDL and MOMENT, to support and guide our development. The requirements of our envisaged Information and Data models are driven from a concrete use-case, using PlanetLab and FEDERICA as examples of virtualized platforms in a Future Internet federated environment.

ETOMIC Advanced Network Monitoring System for Future Internet Experimentation

ETOMIC is a network traffic measurement platform with high precision GPS-synchronized monitoring nodes. The infrastructure is publicly available to the network research community, supporting advanced experimental techniques by providing high precision hardware equipments and a Central Management System. Researchers can deploy their own active measurement codes to perform experiments on the public Internet. Recently, the functionalities of the original system were significantly extended and new generation measurement nodes were deployed. The system now also includes well structured data repositories to archive and share raw and evaluated data. These features make ETOMIC as one of the experimental facilities that support the design, development and validation of novel experimental techniques for the future Internet. In this paper we focus on the improved capabilities of the management system, the recent extensions of the node architecture and the accompanying database solutions.

Measuring the dimension of partially embedded networks

Scaling phenomena have been intensively studied during the past decade in the context of complex networks. As part of these works, recently novel methods have appeared to measure the dimension of abstract and spatially embedded networks. In this paper we propose a new dimension measurement method for networks, which does not require global knowledge on the embedding of the nodes, instead it exploits link-wise information (link lengths, link delays or other physical quantities). Our method can be regarded as a generalization of the spectral dimension, that grasps the network’s large-scale structure through local observations made by a random walker while traversing the links. We apply the presented method to synthetic and real-world networks, including road maps, the Internet infrastructure and the Gowalla geosocial network. We analyze the theoretically and empirically designated case when the length distribution of the links has the form P(ρ)∼1/ρ. We show that while previous dimension concepts are not applicable in this case, the new dimension measure still exhibits scaling with two distinct scaling regimes. Our observations suggest that the link length distribution is not sufficient in itself to entirely control the dimensionality of complex networks, and we show that the proposed measure provides information that complements other known measures.

A Monitoring Framework for Federated Virtualized Infrastructures

Monitoring and measurement is a fundamental building block for developing and testing new protocols, routing algorithms and networked applications. In a federated virtualized testbed they allow other service components and testbed-users to follow the current state of the network, and on the other hand they enable intelligent automatic decision-making, e.g. during the embedding of a virtual topology. However, it is not a trivial task to enable federated monitoring functionalities due to the cross-domain nature of the system. The heterogeneity of the federated networks (including network elements and monitoring tools) pose a major challenge. In this chapter we present a framework that tackles some of the most important related problems. We also introduce a specific ontology to describe monitoring and network measurement tasks. This semantic approach enables the flexible integration of a wide range of monitoring tools, metrics and databases. Our Monitoring Framework was created within the NOVI FP7 STREP project which federates two major virtualized testbeds, PlanetLab and Federica.

Network Measurement Virtual Observatory: An Integrated Database Environment for Internet Research and Experimentation

To understand the long-term dynamics of networks engineers and network scientists collect tremendous amount of data and distribute them across many different data warehouses. In EU FP7 OpenLab project we developed the nmVO, which helps handling distinct data sources together in a common way efficiently. It also supports data collecting systems with a permanent data storage, such as SONoMA, and provides a public front-end to run measurements and access data, called GrayWulf. Furthermore, the on-line analysis of data, yielding the behavior and the structure of the Internet is convenient by using server side scientific functionalities.