Available Bandwidth Estimation Tools Metrics, Approaches and Performance

The estimation of the available bandwidth (av bw) between two end nodes through the Internet, is an area that has motivated researchers around the world in the last twenty years, to have faster and more accurate tools; Due to the utility it has in various network applications; Such as routing management, intrusion detection systems and the performance of transport protocols. Different tools use different estimation techniques but generally only analyze the three most used metrics as av bw, relative error and estimation time. This work expands the information regarding the evaluation literature of the current Available Bandwidth Estimation Tools (ABET’s), where they analyze the estimation techniques, metrics, different generation tools of cross-traf?c and evaluation testbed; Concentrating on the techniques and estimation methodologies used, as well as the challenges faced by open-source tools in high-performance networks of 10Gbps or higher

Available Bandwidth Estimation Tools Metrics, Approaches and Performance

The estimation of the available bandwidth (av_bw) between two end nodes through the Internet, is an area that has motivated researchers around the world in the last twenty years, to have faster and more accurate tools; Due to the utility it has in various network applications; Such as routing management, intrusion detection systems and the performance of transport protocols. Different tools use different estimation techniques but generally only analyze the three most used metrics as av_bw, relative error and estimation time. This work expands the information regarding the evaluation literature of the current Available Bandwidth Estimation Tools (ABET's), where they analyze the estimation techniques, metrics, different generation tools of cross-traffic and evaluation testbed; Concentrating on the techniques and estimation methodologies used, as well as the challenges faced by open-source tools in high-performance networks of 10 Gbps or higher

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

Performance Analysis of Available Bandwidth Estimation Tools for Grid Networks

Abstract Modern large-scale grid computing systems for processing advanced science and engineering applications rely on geographically distributed clusters. In such highly distributed environments, estimating the available bandwidth between clusters is a key issue for efficient task scheduling. We analyze the performance of two well known available bandwidth estimation tools, pathload and abget, with the aim of using them in grid environments. Our experiments consider the accuracy of the estimation, the convergence time, their level of intrusion in the grid links, and the ability to handle multiple simultaneous estimations. Overall, pathload represents a good solution to estimate available bandwidth in grid environments

Spectral analysis of coronary bypass doppler blood flow signals

Dissertação de mest., Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011The pulsed Doppler ultrasound (DU) is one of the important tools in the study of vessel diseases and the investigation of flow conditions. Due to its non-invasive nature, it has been increasingly used in medicine in the last few decades. Accurate estimation of DU spectral center frequency and bandwidth parameters are extremely important for blood flow diagnostic purposes. Under real-time data acquisition conditions the DU signal is generally corrupted with different types of noise. In these situations the identification of signal components solely belonging to the blood flow signal is a difficult task. This thesis was aimed to study spectral techniques to enhance spectral parameter estimation, in particular the center frequency. Spectral estimates were obtained using the Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT). STFT was applied to short duration data segments, respecting signals’ stationary properties. Two CWT functions have been studied: varying bandwidth filter and fixed bandwidth filter. Since different filter bandwidth values yield different results, bandwidths for fixed bandwidth filter were investigate and the most proper one has been used on the performance comparative studies. To enhance the blood flow signal content of noise-embedded clinical Doppler signals, a STFT-based technique was proposed to reduce the signals’ noise components. Quantitative evaluation of the spectral methods was primarily performed on simulated signals with deterministic center frequency and bandwidth. Different signal to noise ratio signals were simulated. It has been observed that STFT spectral center frequency and bandwidth estimators were less biased than the CWT ones, although the last ones were less sensitive to the center frequency variations. Applying the proposed noise cancellation technique to simulated signals reduces the spectral estimators’ errors. As an example, a typical noisy signal with 10dbSNR, a reduction of 88% and 97% was obtained on the RMS bias of the estimation of the center frequency and bandwidth estimators respectively

The Quest for Bandwidth Estimation Techniques for large-scale Distributed Systems

In recent years the research community has developed many techniques to estimate the end-to-end available bandwidth of an Internet path. This important metric has been proposed for use in several distributed systems and, more recently, has even been considered to improve the congestion control mechanism of TCP. Thus, it has been suggested that some existing estimation techniques could be used for this purpose. However, existing tools were not designed for large-scale deployments and were mostly validated in controlled settings, considering only one measurement running at a time. In this paper, we argue that current tools, while offering good estimates when used alone, might not work in large-scale systems where several estimations severely interfere with each other. We analyze the properties of the measurement paradigms employed today and discuss their functioning, study their overhead and analyze their interference. Our testbed results show that current techniques are insufficient as they are. Finally, we will discuss and propose some principles that should be taken into account for including available bandwidth measurements in large-scale distributed systems. 1

Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview

Disturbance Observer has been one of the most widely used robust control tools since it was proposed in 1983. This paper introduces the origins of Disturbance Observer and presents a survey of the major results on Disturbance Observer-based robust control in the last thirty-five years. Furthermore, it explains the analysis and synthesis techniques of Disturbance Observer-based robust control for linear and nonlinear systems by using a unified framework. In the last section, this paper presents concluding remarks on Disturbance Observer-based robust control and its engineering applications.Comment: 12 pages, 4 figure