A Graph Theoretic Perspective on Internet Topology Mapping

Understanding the topological characteristics of the Internet is an important research issue as the Internet grows with no central authority. Internet topology mapping studies help better understand the structure and dynamics of the Internet backbone. Knowing the underlying topology, researchers can better develop new protocols and services or fine-tune existing ones. Subnet-level Internet topology measurement studies involve three stages: topology collection, topology construction, and topology analysis. Each of these stages contains challenging tasks, especially when large-scale backbone topologies of millions of nodes are studied. In this dissertation, I first discuss issues in subnet-level Internet topology mapping and review state-of-the-art approaches to handle them. I propose a novel graph data indexing approach to to efficiently process large scale topology data. I then conduct an experimental study to understand how the responsiveness of routers has changed over the last decade and how it differs based on the probing mechanism. I then propose an efficient unresponsive resolution approach by incorporating our structural graph indexing technique. Finally, I introduce Cheleby, an integrated Internet topology mapping system. Cheleby first dynamically probes observed subnetworks using a team of PlanetLab nodes around the world to obtain comprehensive backbone topologies. Then, it utilizes efficient algorithms to resolve subnets, IP aliases, and unresponsive routers in the collected data sets to construct comprehensive subnet-level topologies. Sample topologies are provided at http://cheleby.cse.unr.edu

The Impact of Name-Matching and Blocking on Author Disambiguation

In this work, we address the problem of blocking in the context of author name disambiguation. We describe a framework that formalizes different ways of name-matching to determine which names could potentially refer to the same author. We focus on name variations that follow from specifying a name with different completeness (i.e. full first name or only initial). We extend this framework by a simple way to define traditional, new and custom blocking schemes. Then, we evaluate different old and new schemes in the Web of Science. In this context we define and compare a new type of blocking schemes. Based on these results, we discuss the question whether name-matching can be used in blocking evaluation as a replacement of annotated author identifiers. Finally, we argue that blocking can have a strong impact on the application and evaluation of author disambiguation

Etude rétrospective sur l'évolution clinique d'une cohorte de patients avec polyarthrite rhumatoïde traités par inhibiteurs du TNF-α

Cette étude rétrospective incluant 66 patients avec polyarthrite rhumatoïde de longue durée et résistant à plusieurs traitements de fond a permis d'analyser les réponses cliniques, biologiques et radiologiques en réponse aux inhibiteurs du TNF-α. Cette étude offre l'avantage d'analyser de nombreux paramètres cliniques (DAS, RADAI, HAQ, Douleurs), biologiques (VS, CRP) ainsi que l'évolution radiologique dans une population non sélectionnée. Les résultats obtenus corroborent les données de la littérature. Après introduction des traitements par des inhibiteurs du TNF-α, les index cliniques, biologiques et radiologiques s'améliorent significativement à 6, 12 et à plus de 20 mois de suivi. En ce qui concerne le maintient du traitement jusqu'au terme de l'étude et les effets secondaires, nos résultats sont comparables aux données de la littérature

Graph Data Mining to Construct Sampled Internet Topology Maps

Understanding the topological characteristics of the Internet is important for researchers and practitioners as the Internet grows with no central authority. This understanding is a necessity to better design, implement, protect and operate the underlying network technologies, protocols, and services. The need for accurate Internet topology map has increased recently with new services such as overlay networks and IP TV. Router-level Internet topology measurement studies have three main steps: topology collection, topology construction, and topology analysis. In topology construction, there are several main challenges: unresponsive router resolution, identification of underlying subnets and detection of IP aliases. These tasks become especially challenging when large-scale topologies of millions of nodes are studied. In this thesis, we present the topology construction processes of the Cheleby system, an Internet topology mapping system that provides insight into the Internet topology by taking daily snapshots of the underlying networks. The system utilizes efficient algorithms to process large-scale datasets collected from distributed vantage points and provides accurate topology graphs at link layer. Incorporating enhanced resolution algorithms, Cheleby provides comprehensive Internet backbone maps

CCF: Fast and scalable connected component computation in MapReduce

Abstract—Finding connected components in a graph is a well-known problem in a wide variety of application areas such as social network analysis, data mining, image processing, and etc. In this paper, we present an efficient and scalable approach in MapReduce to find all the connected components in a given graph. We compare our approach with the state-of-the-art on a real-world graph. We also demonstrate the viability of our approach on a massive graph with ∼6B nodes and ∼92B edges on an 80-node hadoop cluster. To the best of our knowledge, this is the largest graph publicly used in such an experiment

2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining Six Degrees of Separation among US Researchers

Abstract—Funding from the government agencies has been the driving force for the research and educational institutions particularly in the United States. The government funds billions of dollars every year to lead research initiatives that will shape the future. In this paper, we analyze the funds distributed by the National Science Foundation (NSF), a major source of research funding in the States, to understand the collaboration patterns among researchers and institutions. Using complex network analysis, we interpret the collaboration patterns at researcher, institution and state levels by constructing the corresponding networks based on the number of grants collaborated. We further analyze the directorates to identify the differences in collaboration trends between disciplines. Keywords-Complex networks; Complex network analysis; Research funding networks; Six degrees of separation; NSF. I