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On Identifying Additive Link Metrics Using Linearly Independent Cycles and Paths
 ACCEPTED FOR PUBLICATION IN IEEE/ACM TRANSACTIONS ON NETOWRKING
, 2011
"... In this paper, we study the problem of identifying constant additive link metrics using linearly independent monitoring cycles and paths. A monitoring cycle starts and ends at the same monitoring station while a monitoring path starts and ends at distinct monitoring stations. We show that three edge ..."
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In this paper, we study the problem of identifying constant additive link metrics using linearly independent monitoring cycles and paths. A monitoring cycle starts and ends at the same monitoring station while a monitoring path starts and ends at distinct monitoring stations. We show that three edge connectivity is a necessary and sufficient condition to identify link metrics using one monitoring station and employing monitoring cycles. We develop a polynomial time algorithm to compute the set of linearly independent cycles. For networks that are less than threeedge connected, we show how the minimum number of monitors required and their placement may be computed. For networks with symmetric directed links, we show the relationship between the number of monitors employed, the number of directed links for which metric is known a priori, and the identifiability for the remaining links. To the best of our knowledge, this is the first work that derives the necessary and sufficient conditions on the network topology for identifying additive link metrics and develops a polynomial time algorithm to compute linearly independent cycles and paths.
Statistical Aspects of the Analysis of Data Networks
"... Assessing and monitoring the performance of computer and communications networks is an important problem for network engineers. There has been a considerable amount of work on tools and techniques for data collection, modeling, and analysis within the network research community. The goal of this pap ..."
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Assessing and monitoring the performance of computer and communications networks is an important problem for network engineers. There has been a considerable amount of work on tools and techniques for data collection, modeling, and analysis within the network research community. The goal of this paper is to present an overview of the engineering problems and statistical issues, describe recent research developments, and summarize ongoing work and areas for further research. While there are many interesting issues related to network analysis, our focus here is on estimating and monitoring network QualityofService parameters. We discuss methods for estimating edgelevel parameters from endtoend pathlevel measurements, an important engineering problem that raises interesting statistical modeling issues. Other topics include network monitoring, network visualization, and discovering network topology. Data from a corporate network are used to illustrate the problems and techniques. As in any overview paper, the discussion is likely to be slanted towards our own research interests.
A Network Coding Approach to Loss Tomography
"... Abstract—Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of interest is the loss rate of individual links and multicast and/or unicast endtoend probes are typically used. I ..."
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Abstract—Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of interest is the loss rate of individual links and multicast and/or unicast endtoend probes are typically used. Independently, recent advances in network coding have shown that there are advantages from allowing intermediate nodes to process and combine, in addition to just forward, packets. In this paper, we study the problem of loss tomography in networks with network coding capabilities. We design a framework for estimating link loss rates, which leverages network coding capabilities, and we show that it improves several aspects of tomography, including the identifiability of links, the tradeoff between estimation accuracy and bandwidth efficiency, and the complexity of probe path selection. We discuss the cases of inferring link loss rates in a tree topology and in a general topology. In the latter case, the benefits of our approach are even more pronounced compared to standard techniques but we also face novel challenges, such as dealing with cycles and multiple paths between sources and receivers. Overall, this work makes the connection between active network tomography and network coding. Index Terms—Link loss inference, network coding, network tomography. I.
TRANSACTIONS ON SIGNAL PROCESSING 1 Fast, MomentBased Estimation Methods for Delay Network Tomography
, 2008
"... Consider the delay network tomography problem where the goal is to estimate distributions of delays at the linklevel using data on endtoend delays. These measurements are obtained using probes that are injected at nodes located on the periphery of the network and sent to other nodes also located ..."
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Consider the delay network tomography problem where the goal is to estimate distributions of delays at the linklevel using data on endtoend delays. These measurements are obtained using probes that are injected at nodes located on the periphery of the network and sent to other nodes also located on the periphery. Much of the previous literature deals with discrete delay distributions by discretizing the data into small bins. This paper considers more general models with a focus on computationally efficient estimation. The momentbased schemes presented here are designed to function well for larger networks and for applications like monitoring that require speedy solutions. EDICS: SSPDECO, SSPHIER, SSPNGAU, SSPPARE
Problèmes inverses dans les réseaux Inverse problems in Networks
, 2013
"... (Ecole doctorale: Informatique, télécommunications et électronique (ED 130)) présentée par ..."
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(Ecole doctorale: Informatique, télécommunications et électronique (ED 130)) présentée par