Network Kriging

Network service providers and customers are often concerned with aggregate performance measures that span multiple network paths. Unfortunately, forming such network-wide measures can be difficult, due to the issues of scale involved. In particular, the number of paths grows too rapidly with the number of endpoints to make exhaustive measurement practical. As a result, it is of interest to explore the feasibility of methods that dramatically reduce the number of paths measured in such situations while maintaining acceptable accuracy. We cast the problem as one of statistical prediction--in the spirit of the so-called `kriging' problem in spatial statistics--and show that end-to-end network properties may be accurately predicted in many cases using a surprisingly small set of carefully chosen paths. More precisely, we formulate a general framework for the prediction problem, propose a class of linear predictors for standard quantities of interest (e.g., averages, totals, differences) and show that linear algebraic methods of subset selection may be used to effectively choose which paths to measure. We characterize the performance of the resulting methods, both analytically and numerically. The success of our methods derives from the low effective rank of routing matrices as encountered in practice, which appears to be a new observation in its own right with potentially broad implications on network measurement generally.Comment: 16 pages, 9 figures, single-space

On Delays in Management Frameworks: Metrics, Models and Analysis

Management performance evaluation means assessment of scalability, complexity, accuracy, throughput, delays and resources consumptions. In this paper, we focus on the evaluation of management frameworks delays through a set of specific metrics. We investigate the statistical properties of these metrics when the number of management nodes increases. We show that management delays measured at the application level are statistically modeled by distributions with heavy tails, especially the Weibull distribution. Given that delays can substantially degrade the capacity of management algorithms to react and resolve problems it is useful to get a finer model to describe them.We suggest theWeibull distribution as a model of delays for the analysis and simulations of such algorithms

Estimating the access link quality by active measurements

International audienceThe access link quality experienced by the end users depends on the amount of traffic and on the presence of network anomalies. Different techniques exist to detect anomalies, but little attention has been devoted to quantify the access link quality and to which extent network anomalies affect the end user's access link experience. We refer to this aspect as the impact factor of the anomaly, that we define as the percentage of affected destinations. In the ideal case, a node should continuously monitor all possible routes to detect any degradation in performance, but this is not practical in reality. In this paper we show how a node can estimate the quality of Internet access through a limited set of measurements. We initially study the user's access network to understand the typical features of its connectivity tree. Then, we define an unbiased estimator for the quality of access and we compute the minimum number of paths to monitor, so that the estimator achieves a desirable accuracy without knowing the underlying topology. We use real data to construct a network graph and we validate our solution by causing a large number of anomalies and by comparing the real and the estimated quality of access for all available end hosts. Our results show that the impact factor is a meaningful metric to evaluate the quality of Internet access

Data Driven Network Design for Cloud Services Based on Historic Utilization

In recent years we have seen a shift from traditional networking in enterprises with Data Center centric architectures moving to cloud services. Companies are moving away from private networking technologies like MPLS as they migrate their application workloads to the cloud. With these migrations, network architects must struggle with how to design and build new network infrastructure to support the cloud for all their end users including office workers, remote workers, and home office workers. The main goal for network design is to maximize availability and performance and minimize cost. However, network architects and network engineers tend to over provision networks by sizing the bandwidth for worst case scenarios wasting millions of dollars per year. This thesis will analyze traditional network utilization data from twenty-five of the Fortune 500 companies in the United States and determine the most efficient bandwidth to support cloud services from providers like Amazon, Microsoft, Google, and others. The analysis of real-world data and the resulting proposed scaling factor is an original contribution from this study

ROUTING TOPOLOGY RECOVERY FOR WIRELESS SENSOR NETWORKS

Liu, Rui Ph.D., Purdue University, December 2014. Routing Topology Recovery for Wireless Sensor Networks. Major Professor: Yao Liang

Efficient techniques for end-to-end bandwidth estimation: performance evaluations and scalable deployment

Several applications, services, and protocols are conjectured to benefit from the knowledge of the end-to-end available bandwidth on a given Internet path. Unfortunately, despite the availability of several bandwidth estimation techniques, there has been only a limited adoption of these in contemporary applications. We identify two issues that contribute to this state of affairs. First, there is a lack of comprehensive evaluations that can help application developers in calibrating the relative performance of these tools--this is especially limiting since the performance of these tools depends on algorithmic, implementation, as well as temporal aspects of probing for available bandwidth. Second, most existing bandwidth estimation tools impose a large probing overhead on the paths over which bandwidth is measured. This can be a significant deterrent for deploying these tools in distributed infrastructures that need to measure bandwidth on several paths periodically. In this dissertation, we address the two issues raised above by making the following contributions: We conduct the first comprehensive black-box evaluation of a large suite of prominent available bandwidth estimation tools on a high-speed network. In this evaluation,we also illustrate the impact that technological and implementation limitations can have on the performance of bandwidth-estimation tools. We conduct the first comprehensive evaluation of available bandwidth estimation algorithms, independent of systemic and implementation biases. In this evaluation, we also illustrate the impact temporal factor such as measurement timescales have on the observed relative performance of bandwidth-estimation tools. We demonstrate that temporal properties can significantly impact the AB estimation process. We redesign the interfaces of existing bandwidth-estimation tools to allow temporal parameters to be explicitly specified and controlled. We design AB inference schemes which can be used to scalably and collaboratively infer the available bandwidth for a large set of end-to-end paths. These schemes allow an operator to select the desired operating point in the trade-off between accuracy and overhead of AB estimation. We further demonstrate that in order to monitor the bandwidth on all paths of a network we do not need access to per-hop bandwidth estimates and can simply rely on end-to-end bandwidth estimates

Contribuciones basadas en el análisis biplot al diseño y gestión de redes de telecomunicación

[ES] La importancia de la redes de telecomunicación en nuestra sociedad es innegable. Desde la telefonía, tanto fija como móvil, hasta la red Internet están presentes en la mayoría de los hogares, empresas y administraciones públicas. Garantizar su correcto funcionamiento es de una importancia clave y la herramienta fundamental para este objetivo es un adecuado diseño y gestión de la red. Los métodos biplot, formulados por Gabriel en 1971, permiten representar una matriz de datos en forma de un gráfico que utiliza marcadores individuales para cada una de las filas y las columnas de la matriz de partida, respetando determinadas propiedades de los datos originales. En el diseño y gestión de redes se pueden utilizar múltiples tipos de matrices conteniendo diversos datos sobre su operación y configuración. Destacan entre ellas las matrices de tráfico, las matrices de topología y combinaciones de ambas. Por otro lado, las representaciones gráficas permiten a los diseñadores y gestores de la red identificar de manera eficiente y eficaz el estado de la red de comunicaciones. Esta tesis doctoral propone la utilización de los métodos biplot, en general, y del HJ-Biplot, propuesto por Galindo en 1986, en particular, en los procesos de diseño y gestión de redes de comunicación, presentando aplicaciones sobre las redes de datos más habituales hoy en día. Las propuestas se centran en tres casuísticas generales que cubren un amplio espectro de posibles aplicaciones: detección de anomalías, análisis de series temporales de tráfico y análisis de la topología de redes. La detección de anomalías se aplica en un primer ejemplo sobre datos de una red Ethernet real. Se demuestra que es posible utilizar la representación HJ-Biplot con dos objetivos: modelar la red con una representación adecuadamente robusta y detectar incidencias con la suficiente sensibilidad. En un segundo supuesto se aplica a la detección de un ataque de negación de servicio, como caso especial de anomalía, para lo que se utiliza un juego de datos publicados para la verificación del funcionamiento de este tipo de sistemas. En este apartado se incluye la aplicación del método STATIS para la detección de la anomalía, y finalmente el HJ-Biplot para la diagnosis concreta de la incidencia ocurrida en la red. El análisis de series temporales utilizando el HJ-Biplot mejora la propuesta realizada por Lakhina et al en 2004 y siguientes, que aplicaba el Análisis de Componentes Principales (ACP) a una matriz de tráfico Origen-Destino. El HJ-Biplot tiene en consideración la existencia simultánea de correlaciones temporales y espaciales en la matriz de tráfico y además permite localizar el punto de ocurrencia de la incidencia. Finalmente, la combinación de la teoría espectral de grafos, aplicada a redes de comunicación, y la metodología biplot en general, y el HJ-Biplot en particular, permite obtener representaciones gráficas de las redes de comunicación con información sobre su topología, incluso incorporando información sobre tráfico cursado, simétrico o asimétrico, entre nodos. La tesis doctoral presenta algunas contribuciones de los métodos biplot al análisis y gestión de las redes de comunicación más utilizadas en nuestros días. La herramienta propuesta permite mejorar los procedimientos de diseño y gestión de redes constituyendo una potente herramienta de visualización del estado de la red de comunicación

Efficient Monitoring of End-to-End Network Properties

It is often desirable to monitor end-to-end properties, such as loss rates or packet delays, across an entire network. However, active end-to-end measurement in such settings does not scale well, and so complete network-wide measurement quickly becomes infeasible. More efficient measurement strategies are therefore needed