195 research outputs found

    An integrated transport solution to big data movement in high-performance networks

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    Extreme-scale e-Science applications in various domains such as earth science and high energy physics among multiple national institutions within the U.S. are generating colossal amounts of data, now frequently termed as “big data”. The big data must be stored, managed and moved to different geographical locations for distributed data processing and analysis. Such big data transfers require stable and high-speed network connections, which are not readily available in traditional shared IP networks such as the Internet. High-performance networking technologies and services featuring high bandwidth and advance reservation are being rapidly developed and deployed across the nation and around the globe to support such scientific applications. However, these networking technologies and services have not been fully utilized, mainly because: i) the use of these technologies and services often requires considerable domain knowledge and many application users are even not aware of their existence; and ii) the end-to-end data transfer performance largely depends on the transport protocol being used on the end hosts. The high-speed network path with reserved bandwidth in High-performance Networks has shifted the data transfer bottleneck from network segments in traditional IP networks to end hosts, which most existing transport protocols are not well suited to handle. In this dissertation, an integrated transport solution is proposed in support of data- and network-intensive applications in various science domains. This solution integrates three major components, i.e., i) transport-support workflow optimization, ii) transport profile generation, and iii) transport protocol design, into a unified framework. Firstly, a class of transport-support workflow optimization problems are formulated, where an appropriate set of resources and services are selected to compose the best transport-support workflow to meet user’s data transfer request in terms of various performance requirements. Secondly, a transport profiler named Transport Profile Generator (TPG) and its extended and accelerated version named FastProf are designed and implemented to characterize and enhance the end-to-end data transfer performance of a selected transport method over an established network path. Finally, several approaches based on rate and error threshold control are proposed to design a suite of data transfer protocols specifically tailored for big data transfer over dedicated connections. The proposed integrated transport solution is implemented and evaluated in: i) a local testbed with a single 10 Gb/s back-to-back connection and dual 10 Gb/s NIC-to-NIC connections; and ii) several wide-area networks with 10 Gb/s long-haul connections at collaborative sites including Oak Ridge National Laboratory, Argonne National Laboratory, and University of Chicago

    Performance Optimization and Dynamics Control for Large-scale Data Transfer in Wide-area Networks

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    Transport control plays an important role in the performance of large-scale scientific and media streaming applications involving transfer of large data sets, media streaming, online computational steering, interactive visualization, and remote instrument control. In general, these applications have two distinctive classes of transport requirements: large-scale scientific applications require high bandwidths to move bulk data across wide-area networks, while media streaming applications require stable bandwidths to ensure smooth media playback. Unfortunately, the widely deployed Transmission Control Protocol is inadequate for such tasks due to its performance limitations. The purpose of this dissertation is to conduct rigorous analytical study of the design and performance of transport solutions, and develop an integrated transport solution in a systematical way to overcome the limitations of current transport methods. One of the primary challenges is to explore and compose a set of feasible route options with multiple constraints. Another challenge essentially arises from the randomness inherent in wide-area networks, particularly the Internet. This randomness must be explicitly accounted for to achieve both goodput maximization and stabilization over the constructed routes by suitably adjusting the source rate in response to both network and host dynamics.The superior and robust performance of the proposed transport solution is extensively evaluated in a simulated environment and further verified through real-life implementations and deployments over both Internet and dedicated connections under disparate network conditions in comparison with existing transport methods

    Transport Layer solution for bulk data transfers over Heterogeneous Long Fat Networks in Next Generation Networks

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    Aquesta tesi per compendi centra les seves contribucions en l'aprenentatge i innovació de les Xarxes de Nova Generació. És per això que es proposen diferents contribucions en diferents àmbits (Smart Cities, Smart Grids, Smart Campus, Smart Learning, Mitjana, eHealth, Indústria 4.0 entre d'altres) mitjançant l'aplicació i combinació de diferents disciplines (Internet of Things, Building Information Modeling, Cloud Storage, Ciberseguretat, Big Data, Internet de el Futur, Transformació Digital). Concretament, es detalla el monitoratge sostenible del confort a l'Smart Campus, la que potser es la meva aportació més representativa dins de la conceptualització de Xarxes de Nova Generació. Dins d'aquest innovador concepte de monitorització s'integren diferents disciplines, per poder oferir informació sobre el nivell de confort de les persones. Aquesta investigació demostra el llarg recorregut que hi ha en la transformació digital dels sectors tradicionals i les NGNs. Durant aquest llarg aprenentatge sobre les NGN a través de les diferents investigacions, es va poder observar una problemàtica que afectava de manera transversal als diferents camps d'aplicació de les NGNs i que aquesta podia tenir una afectació en aquests sectors. Aquesta problemàtica consisteix en el baix rendiment durant l'intercanvi de grans volums de dades sobre xarxes amb gran capacitat d'ample de banda i remotament separades geogràficament, conegudes com a xarxes elefant. Concretament, això afecta al cas d'ús d'intercanvi massiu de dades entre regions Cloud (Cloud Data Sharing use case). És per això que es va estudiar aquest cas d'ús i les diferents alternatives a nivell de protocols de transport,. S'estudien les diferents problemàtiques que pateixen els protocols i s'observa per què aquests no són capaços d'arribar a rendiments òptims. Deguda a aquesta situació, s'hipotetiza que la introducció de mecanismes que analitzen les mètriques de la xarxa i que exploten eficientment la capacitat de la mateixa milloren el rendiment dels protocols de transport sobre xarxes elefant heterogènies durant l'enviament massiu de dades. Primerament, es dissenya l’Adaptative and Aggressive Transport Protocol (AATP), un protocol de transport adaptatiu i eficient amb l'objectiu de millorar el rendiment sobre aquest tipus de xarxes elefant. El protocol AATP s'implementa i es prova en un simulador de xarxes i un testbed sota diferents situacions i condicions per la seva validació. Implementat i provat amb èxit el protocol AATP, es decideix millorar el propi protocol, Enhanced-AATP, sobre xarxes elefant heterogènies. Per això, es dissenya un mecanisme basat en el Jitter Ràtio que permet fer aquesta diferenciació. A més, per tal de millorar el comportament del protocol, s’adapta el seu sistema de fairness per al repartiment just dels recursos amb altres fluxos Enhanced-AATP. Aquesta evolució s'implementa en el simulador de xarxes i es realitzen una sèrie de proves. A l'acabar aquesta tesi, es conclou que les Xarxes de Nova Generació tenen molt recorregut i moltes coses a millorar causa de la transformació digital de la societat i de l'aparició de nova tecnologia disruptiva. A més, es confirma que la introducció de mecanismes específics en la concepció i operació dels protocols de transport millora el rendiment d'aquests sobre xarxes elefant heterogènies.Esta tesis por compendio centra sus contribuciones en el aprendizaje e innovación de las Redes de Nueva Generación. Es por ello que se proponen distintas contribuciones en diferentes ámbitos (Smart Cities, Smart Grids, Smart Campus, Smart Learning, Media, eHealth, Industria 4.0 entre otros) mediante la aplicación y combinación de diferentes disciplinas (Internet of Things, Building Information Modeling, Cloud Storage, Ciberseguridad, Big Data, Internet del Futuro, Transformación Digital). Concretamente, se detalla la monitorización sostenible del confort en el Smart Campus, la que se podría considerar mi aportación más representativa dentro de la conceptualización de Redes de Nueva Generación. Dentro de este innovador concepto de monitorización se integran diferentes disciplinas, para poder ofrecer información sobre el nivel de confort de las personas. Esta investigación demuestra el recorrido que existe en la transformación digital de los sectores tradicionales y las NGNs. Durante este largo aprendizaje sobre las NGN a través de las diferentes investigaciones, se pudo observar una problemática que afectaba de manera transversal a los diferentes campos de aplicación de las NGNs y que ésta podía tener una afectación en estos sectores. Esta problemática consiste en el bajo rendimiento durante el intercambio de grandes volúmenes de datos sobre redes con gran capacidad de ancho de banda y remotamente separadas geográficamente, conocidas como redes elefante, o Long Fat Networks (LFNs). Concretamente, esto afecta al caso de uso de intercambio de datos entre regiones Cloud (Cloud Data Data use case). Es por ello que se estudió este caso de uso y las diferentes alternativas a nivel de protocolos de transporte. Se estudian las diferentes problemáticas que sufren los protocolos y se observa por qué no son capaces de alcanzar rendimientos óptimos. Debida a esta situación, se hipotetiza que la introducción de mecanismos que analizan las métricas de la red y que explotan eficientemente la capacidad de la misma mejoran el rendimiento de los protocolos de transporte sobre redes elefante heterogéneas durante el envío masivo de datos. Primeramente, se diseña el Adaptative and Aggressive Transport Protocol (AATP), un protocolo de transporte adaptativo y eficiente con el objetivo maximizar el rendimiento sobre este tipo de redes elefante. El protocolo AATP se implementa y se prueba en un simulador de redes y un testbed bajo diferentes situaciones y condiciones para su validación. Implementado y probado con éxito el protocolo AATP, se decide mejorar el propio protocolo, Enhanced-AATP, sobre redes elefante heterogéneas. Además, con tal de mejorar el comportamiento del protocolo, se mejora su sistema de fairness para el reparto justo de los recursos con otros flujos Enhanced-AATP. Esta evolución se implementa en el simulador de redes y se realizan una serie de pruebas. Al finalizar esta tesis, se concluye que las Redes de Nueva Generación tienen mucho recorrido y muchas cosas a mejorar debido a la transformación digital de la sociedad y a la aparición de nueva tecnología disruptiva. Se confirma que la introducción de mecanismos específicos en la concepción y operación de los protocolos de transporte mejora el rendimiento de estos sobre redes elefante heterogéneas.This compendium thesis focuses its contributions on the learning and innovation of the New Generation Networks. That is why different contributions are proposed in different areas (Smart Cities, Smart Grids, Smart Campus, Smart Learning, Media, eHealth, Industry 4.0, among others) through the application and combination of different disciplines (Internet of Things, Building Information Modeling, Cloud Storage, Cybersecurity, Big Data, Future Internet, Digital Transformation). Specifically, the sustainable comfort monitoring in the Smart Campus is detailed, which can be considered my most representative contribution within the conceptualization of New Generation Networks. Within this innovative monitoring concept, different disciplines are integrated in order to offer information on people's comfort levels. . This research demonstrates the long journey that exists in the digital transformation of traditional sectors and New Generation Networks. During this long learning about the NGNs through the different investigations, it was possible to observe a problematic that affected the different application fields of the NGNs in a transversal way and that, depending on the service and its requirements, it could have a critical impact on any of these sectors. This issue consists of a low performance operation during the exchange of large volumes of data on networks with high bandwidth capacity and remotely geographically separated, also known as Elephant networks, or Long Fat Networks (LFNs). Specifically, this critically affects the Cloud Data Sharing use case. That is why this use case and the different alternatives at the transport protocol level were studied. For this reason, the performance and operation problems suffered by layer 4 protocols are studied and it is observed why these traditional protocols are not capable of achieving optimal performance. Due to this situation, it is hypothesized that the introduction of mechanisms that analyze network metrics and efficiently exploit network’s capacity meliorates the performance of Transport Layer protocols over Heterogeneous Long Fat Networks during bulk data transfers. First, the Adaptive and Aggressive Transport Protocol (AATP) is designed. An adaptive and efficient transport protocol with the aim of maximizing its performance over this type of elephant network.. The AATP protocol is implemented and tested in a network simulator and a testbed under different situations and conditions for its validation. Once the AATP protocol was designed, implemented and tested successfully, it was decided to improve the protocol itself, Enhanced-AATP, to improve its performance over heterogeneous elephant networks. In addition, in order to upgrade the behavior of the protocol, its fairness system is improved for the fair distribution of resources among other Enhanced-AATP flows. Finally, this evolution is implemented in the network simulator and a set of tests are carried out. At the end of this thesis, it is concluded that the New Generation Networks have a long way to go and many things to improve due to the digital transformation of society and the appearance of brand-new disruptive technology. Furthermore, it is confirmed that the introduction of specific mechanisms in the conception and operation of transport protocols improves their performance on Heterogeneous Long Fat Networks

    Study on the Performance of TCP over 10Gbps High Speed Networks

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    Internet traffic is expected to grow phenomenally over the next five to ten years. To cope with such large traffic volumes, high-speed networks are expected to scale to capacities of terabits-per-second and beyond. Increasing the role of optics for packet forwarding and transmission inside the high-speed networks seems to be the most promising way to accomplish this capacity scaling. Unfortunately, unlike electronic memory, it remains a formidable challenge to build even a few dozen packets of integrated all-optical buffers. On the other hand, many high-speed networks depend on the TCP/IP protocol for reliability which is typically implemented in software and is sensitive to buffer size. For example, TCP requires a buffer size of bandwidth delay product in switches/routers to maintain nearly 100\% link utilization. Otherwise, the performance will be much downgraded. But such large buffer will challenge hardware design and power consumption, and will generate queuing delay and jitter which again cause problems. Therefore, improve TCP performance over tiny buffered high-speed networks is a top priority. This dissertation studies the TCP performance in 10Gbps high-speed networks. First, a 10Gbps reconfigurable optical networking testbed is developed as a research environment. Second, a 10Gbps traffic sniffing tool is developed for measuring and analyzing TCP performance. New expressions for evaluating TCP loss synchronization are presented by carefully examining the congestion events of TCP. Based on observation, two basic reasons that cause performance problems are studied. We find that minimize TCP loss synchronization and reduce flow burstiness impact are critical keys to improve TCP performance in tiny buffered networks. Finally, we present a new TCP protocol called Multi-Channel TCP and a new congestion control algorithm called Desynchronized Multi-Channel TCP (DMCTCP). Our algorithm implementation takes advantage of a potential parallelism from the Multi-Path TCP in Linux. Over an emulated 10Gbps network ruled by routers with only a few dozen packets of buffers, our experimental results confirm that bottleneck link utilization can be much better improved by DMCTCP than by many other TCP variants. Our study is a new step towards the deployment of optical packet switching/routing networks

    The Telecommunications and Data Acquisition Report

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    This publication reports on developments in programs managed by JPL's office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground based radio astronomy, it reports on activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, in supporting research and technology, in implementation and in operations. In geodynamics, the publication reports on the application of radio interferometry at microwave frequencies for geodynamic measurements. This publication also reports on implementation and operations for searching the microwave spectrum

    Nonlinear Burn Condition and Kinetic Profile Control in Tokamak Fusion Reactors

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    One of the most promising devices for realizing power production through nuclear fusion is the tokamak. In order to maximize performance, it is preferable that tokamaks achieve operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high fusion gain, the ratio of fusion power produced to the external heating power needed to sustain reactions. There are many experimental tokamaks around the world, each exploring different facets of plasma physics and fusion technology. These experiments have reached the point where the power released from fusion is nearly equal to the power input required to heat the plasma. The next experimental step is ITER, which aims to reach a fusion gain exceeding ten for short pulses, and to sustain a gain of five for longer pulses (around 1000 s). In order for ITER to be a success, several challenging control engineering problems must be addressed.Among these challenges is to precisely regulate the plasma density and temperature, or burn condition. Due to the nonlinear and coupled dynamics of the system, modulation of the burn condition (either during ramp-up/shut-down or in response to changing power demands) without a well designed control scheme could result in undesirable transient performance. Feedback control will also be necessary for responding to unexpected changes in plasma confinement, impurity content, or other parameters, which could significantly alter the burn condition during operation. Furthermore, although stable operating points exist for most confinement scalings, certain conditions can lead to thermal instabilities. Such instabilities can either lead to quenching or a thermal excursion in which the system moves to a higher temperature equilibrium point. In any of these situations, disruptive plasma instabilities could be triggered, stopping operation and potentially causing damage to the confinement vessel.In this work, the problem of burn condition control is addressed through the design of a nonlinear control law guaranteeing stability of desired equilibria. Multiple actuation methods, including auxiliary heating, isotopic fueling, and impurity injection, are used to ensure the burn condition is regulated even when actuators saturate. An adaptive control scheme is used to handle model uncertainty, and an online optimization scheme is proposed to ensure that the plasma is driven to an operating point that minimizes an arbitrary cost function. Due to the possible limited availability of diagnostic systems in ITER and future reactors, an output feedback control scheme is also proposed that combines the nonlinear controller with an observer that estimates the states of the burning plasma system based on available measurements. Finally, the control scheme is tested using the integrated modeling code METIS.The control of spatial profiles of parameters, including current, density, and temperature, is also an important challenge in fusion research, due to their effect on MHD stability, non-inductive current drive, and fusion power. In this work, the problem of kinetic profile control in burning plasmas is addressed through a nonlinear boundary feedback control law designed using a technique called backstepping. A novel implementation of the backstepping technique is used that enables the use of both boundary and interior actuation. The backstepping technique is then applied to the problem of current profile control in both low-confinement and high-confinement mode discharges in the DIII-D tokamak based on a first-principles-driven model of the current profile evolution. Both designs are demonstrated in simulations and experimental tests

    A Flexible, Low-Power, Programmable Unsupervised Neural Network Based on Microcontrollers for Medical Applications

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    We present an implementation and laboratory tests of a winner takes all (WTA) artificial neural network (NN) on two microcontrollers (μC) with the ARM Cortex M3 and the AVR cores. The prospective application of this device is in wireless body sensor network (WBSN) in an on-line analysis of electrocardiograph (ECG) and electromyograph (EMG) biomedical signals. The proposed device will be used as a base station in the WBSN, acquiring and analysing the signals from the sensors placed on the human body. The proposed system is equiped with an analog-todigital converter (ADC), and allows for multi-channel acquisition of analog signals, preprocessing (filtering) and further analysis
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