Travelling Without Moving: Discovering Neighborhood Adjacencies

peer reviewedSince the early 2000's, the research community has explored many approaches to discover and study the Internet topology, designing both data collection mechanisms and models. In this paper, we introduce SAGE (Subnet AggrEgation), a new topology discovery tool that infers the hop-level graph of a target network from a single vantage point. SAGE relies on subnet-level data to build a directed acyclic graph of a network modeling how its (meshes of) routers, a.k.a. neighborhoods, are linked together. Using two groundtruth networks and measurements in the wild, we show SAGE accurately discovers links and is consistent with itself upon a change of vantage point. By mapping subnets to the discovered links, the directed acyclic graphs discovered by SAGE can be re-interpreted as bipartite graphs. Using data collected in the wild from both the PlanetLab testbed and the EdgeNet cluster, we demonstrate that such a model is a credible tool for studying computer networks

PLACE DU SUDOSCAN© DANS L’IDENTIFICATION DES NEUROPATHIES AVEC UNE COMPOSANTE PETITES FIBRES CHEZ DES PATIENTS DIABÉTIQUES

peer reviewe

Efficient Multi-Level Measurements and Modeling of Computer Networks

(abstract) Since the 1980’s, the Internet has steadily grown in size to deliver various services to an increasingly large public, which amounts to billions of users as of the beginning of the 2020’s. As a consequence, its infrastructure has considerably evolved too, which prompted the research community to investigate the topology of the Internet at multiple levels. The highest level is the AS-level (Autonomous System), an Autonomous System being a vast computer network operated by a single company, such as an ISP (Internet Service Provider). Not only the way Autonomous Systems communicate with each other has been investigated, but also their internal networks has drawn the attention of the research community, as many works focused on the mapping and the modeling of the router-level, i.e., how routers are interconnected either within a single AS or at the borders of adjacent ASes. The Internet router-level has been investigated not only to discover its structure, but also to understand its dynamics. Starting from the 2000’s, the research community focused on how the routers balance the traffic between several links to handle the increasingly large amount of network traffic, a process which is commonly denoted as load balancing (a form of traffic engineering). Additionnal works on the router-level aimed at characterizing meshes of routers, i.e., routers that are directly connected at the data link layer (or Layer-2) to manage a large number of links as if they were a single router. In the meantime, the research community also explored other levels of the Internet to complement router-level maps, such as a subnet-level, a subnet (short for subnetwork) being a group of network interfaces that can contact each other directly at the data link layer. This thesis aims at designing new topology discovery techniques to efficiently map the intra-domain topologies of large networks by exploring their different levels and the relationships that exist between these levels, all while dealing with the effects of load balancing. Three different levels are investigated: the router-level, the subnet-level, and the hop-level. The hop-level characterizes how routers or meshes exchange packets at the network layer (or Layer-3), and can therefore be used to study the internal forwarding of a network without extensively discovering its router-level. Not only this thesis provides new topology discovery schemes to map each level, but it also combines them to increase their accuracy. In particular, it introduces a new subnet inference methodology that takes advantage of alias resolution (i.e., the process of determining whether or not a group or pair of network interfaces belong to the same device) to solve ambiguous scenarios, as well as a topology mapping scheme that relies on both subnet-level data and alias resolution to build comprehensive hop-level maps of intra-domain topologies. Moreover, these maps can be interpreted with bipartite formalisms to more easily study their topological features. All topology discovery methods developed for this thesis are comprehensively elaborated and assessed in this document. The tools that implement these methods ( WISE and SAGE ), their source code, and the data they could collect on various Autonomous Systems are publicly available

TreeNET: Discovering and Connecting Subnets

peer reviewedSince the early 2000's, the Internet topology has been an attractive and important research topic, either for developing data collection mechanisms, and for analyzing and modeling the network. Beside traditional aspects of the Internet topology (i.e., IP interface, router, and AS levels), recent researches focused on intermediate promising visions of the topology, namely Point-of-Presence (PoP) and subnets (i.e., a set of devices that are located on the same connection medium and that can communicate directly with each other at the link layer). This paper focuses on network subnet discovery by proposing a new tool called treenet. One of the key aspects of treenet is that it builds a tree representing the way subnets are located with respect to each other. This tree allows treenet to obtain additional information on the network, leading to better analysis of the collected data. In this paper, we demonstrate the potential of treenet through the evaluation of its key algorithmic steps and the study of measurements collected from the PlanetLab testbed

Discovering Routers in Load-balanced Paths

peer reviewedUsually, a set of Traceroute measurements collected for a large amount of target IPs contain one or several route hops at which the IP interfaces vary from one measurement to another. These variations occur even if several measurements share the same length and the same last hops. This is likely a consequence of load balancing, a traffic engineering policy which aims at sharing the load to ensure quality of service. In this paper, we consider the problem of conducting alias resolution on IP interfaces discovered via Traceroute and which are involved in load balancing. By conducting alias resolution in such a context, we want to verify if the IP interfaces involved in load balancing belong to unique routers, and more broadly, how relevant is alias resolution in this context. To do so, we use a slightly edited version of TreeNET, a topology discovery tool which relies on a tree-like structure based on Traceroute measurements to map a target domain. The upgraded TreeNET along the measurements described in this paper are both freely available online

Revisiting Subnet Inference WISE-ly

peer reviewedSince the late 90’s, the Internet topology discovery has been an attractive and important research topic, leading, among others, to multiple probing and data analysis tools developed by the research community. This paper looks at the particular problem of discovering subnets (i.e., a set of devices that are located on the same connection medium and that can communicate directly with each other at the link layer). In this paper, we first show that the use of traffic engineering policies may increase the difficulty of subnet inference. We carefully characterize those difficulties and quantify their prevalence in the wild. Next, we introduce WISE (Wide and lInear Subnet inferencE), a novel tool for subnet inference designed to deal with those issues and able to discover subnets on wide ranges of IP addresses in a linear time. Using two groundtruth networks, we demonstrate that WISE performs better than state-of-the-art tools while being competitive in terms of subnet accuracy. We also show, through large-scale measurements, that the selection of vantage point with WISE does not matter in terms of subnet accuracy. Finally, all our code (WISE, data processing, results plotting) and collected data are freely available

Virtual Insanity: Linear Subnet Discovery

Over the past two decades, the research community has developed many approaches to study the Internet topology. In particular, starting from 2007, various tools explored the inference of subnets, i.e., sets of devices located on the same connection medium which can communicate directly with each other at the link layer. In this paper, we first discuss how today's traffic engineering policies increase the difficulty of subnet inference. We carefully characterize typical difficulties and quantify them in the wild. Next, we introduce WISE (Wide and lInear Subnet inferencE), a new tool which tackles those difficulties and discovers, in a linear time, large networks subnets. Based on two ground truth networks, we demonstrate that WISE outperforms state-of-the-art tools. Then, through large-scale measurements, we show that the selection of a vantage point with WISE has a marginal effect regarding accuracy. Finally, we discuss how subnets can be used to infer neighborhoods (i.e., aggregates of subnets located at most one hop from each other). We discuss how these neighborhoods can lead to bipartite models of the Internet and present validation results and an evaluation of neighborhoods in the wild, using WISE. Both our code and data are freely available

Diastematomyelia discovered in adulthood

peer reviewedNous rapportons le cas d’une patiente de 35 ans, présentant des lombocruralgies gauches chroniques dans un contexte post-traumatique, avec découverte fortuite au scanner lombaire d’une anomalie congénitale. Le diagnostic de diastématomyélie, non exceptionnel in utero, est rare à l’âge adulte et repose sur la réalisation d’un bilan iconographique. Nous exposerons les principales malformations associées qui pourraient faire suspecter ce diagnostic de diastématomyélie. La prise en charge ne fait pas encore l’objet d’un consensus et peut, si elle est mal orchestrée, se grever d’une détérioration neurologique invalidante.We report a case of a 35-year-old woman with recurrent lumbar pain and left cruralgia in a post-traumatic context, for which the scanner had made possible the fortuitous diagnostic of a congenital anomaly. The diagnosis of diastematomyelia, which is more frequent in utero, is rare in adulthood and results from the implementation of an iconographic assessment. We will present the major malformations that are associated with diastematomyelia and which could evoke the presence of this malformation. The management of the anomaly is still controversial and can lead, if not done properly, to invalidating neurological deteriorations

Towards a mini-ensemble of Regional Earth System Models for climate services over Belgium

editorial reviewe