232 research outputs found

    Machine learning for Quality of Experience in real-time applications

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    Enhancing User Experience by Extracting Application Intelligence from Network Traffic

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    Internet Service Providers (ISPs) continue to get complaints from users on poor experience for diverse Internet applications ranging from video streaming and gaming to social media and teleconferencing. Identifying and rectifying the root cause of these experience events requires the ISP to know more than just coarse-grained measures like link utilizations and packet losses. Application classification and experience measurement using traditional deep packet inspection (DPI) techniques is starting to fail with the increasing adoption of traffic encryption and is not cost-effective with the explosive growth in traffic rates. This thesis leverages the emerging paradigms of machine learning and programmable networks to design and develop systems that can deliver application-level intelligence to ISPs at scale, cost, and accuracy that has hitherto not been achieved before. This thesis makes four new contributions. Our first contribution develops a novel transformer-based neural network model that classifies applications based on their traffic shape, agnostic to encryption. We show that this approach has over 97% f1-score for diverse application classes such as video streaming and gaming. Our second contribution builds and validates algorithmic and machine learning models to estimate user experience metrics for on-demand and live video streaming applications such as bitrate, resolution, buffer states, and stalls. For our third contribution, we analyse ten popular latency-sensitive online multiplayer games and develop data structures and algorithms to rapidly and accurately detect each game using automatically generated signatures. By combining this with active latency measurement and geolocation analysis of the game servers, we help ISPs determine better routing paths to reduce game latency. Our fourth and final contribution develops a prototype of a self-driving network that autonomously intervenes just-in-time to alleviate the suffering of applications that are being impacted by transient congestion. We design and build a complete system that extracts application-aware network telemetry from programmable switches and dynamically adapts the QoS policies to manage the bottleneck resources in an application-fair manner. We show that it outperforms known queue management techniques in various traffic scenarios. Taken together, our contributions allow ISPs to measure and tune their networks in an application-aware manner to offer their users the best possible experience

    Dual Queue Coupled AQM: Deployable Very Low Queuing Delay for All

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    On the Internet, sub-millisecond queueing delay and capacity-seeking have traditionally been considered mutually exclusive. We introduce a service that offers both: Low Latency Low Loss Scalable throughput (L4S). When tested under a wide range of conditions emulated on a testbed using real residential broadband equipment, queue delay remained both low (median 100--300 μ\mus) and consistent (99th percentile below 2 ms even under highly dynamic workloads), without compromising other metrics (zero congestion loss and close to full utilization). L4S exploits the properties of `Scalable' congestion controls (e.g., DCTCP, TCP Prague). Flows using such congestion control are however very aggressive, which causes a deployment challenge as L4S has to coexist with so-called `Classic' flows (e.g., Reno, CUBIC). This paper introduces an architectural solution: `Dual Queue Coupled Active Queue Management', which enables balance between Scalable and Classic flows. It counterbalances the more aggressive response of Scalable flows with more aggressive marking, without having to inspect flow identifiers. The Dual Queue structure has been implemented as a Linux queuing discipline. It acts like a semi-permeable membrane, isolating the latency of Scalable and `Classic' traffic, but coupling their capacity into a single bandwidth pool. This paper justifies the design and implementation choices, and visualizes a representative selection of hundreds of thousands of experiment runs to test our claims.Comment: Preprint. 17pp, 12 Figs, 60 refs. Submitted to IEEE/ACM Transactions on Networkin

    Modelo de correlación QoS-QoE en un ambiente de aprovisionamiento de servicio de telecomunicaciones OTT-Telco

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    ANTECEDENTES El aprovisionamiento de la Calidad de la Experiencia (QoE) en servicios de telecomunicaciones requiere de sistemas de gestión que permitan monitorizar y controlar la QoE de los usuarios luego de consumir diferentes servicios de internet provistos sobre la red del operador. En efecto, el consumo elevado de datos por parte de los usuarios requiere, a nivel de gestión de la red, la asignación de recursos suficientes para el correcto funcionamiento de los servicios. En particular, la configuración de la Calidad del Servicio (QoS) ofrecida por el operador dentro de su dominio de operación se torna fundamental para proveer un tratamiento apropiado del tráfico, permitiendo que la percepción de la calidad del servicio por parte de los usuarios finales pueda mantenerse dentro del umbral de tolerancia de acuerdo con las políticas establecidas por la compañía de telecomunicaciones (Telco). En consecuencia, un modelo de correlación QoS-QoE es clave en el aprovisionamiento de servicios de internet sobre la infraestructura del operador de telecomunicaciones. OBJETIVOS La presente tesis de doctorado se centra en proponer un modelo de correlación QoS-QoE en un ambiente de aprovisionamiento de servicios de telecomunicaciones OTT-Telco. Para ello, cinco acciones generales deben llevarse a cabo; a saber: () caracterizar los parámetros de QoS que mayor efecto tienen en la degradación de servicios OTT. () determinar las características, condiciones, parámetros y medidas de QoE en la prestación de un servicio OTT. () establecer las condiciones y restricciones de prestación de un servicio OTT en la infraestructura de una Telco que mantenga una buena relación QoS-QoE. () desarrollar un mecanismo de estimación o predicción de QoE con base en los factores de influencia de QoS que afectan la prestación de un servicio OTT. () evaluar experimentalmente el modelo de correlación QoE-QoS. MÉTODOS Para el cumplimiento de los objetivos, se definió un modelo integrado por un macro-componente Conceptualización y otro Operacional. El macro-componente Conceptualización está orientado por el referente metodológico para la construcción de marcos conceptuales de Jabareen, y el macro-componente Operacional está alineado con las fases definidas para el desarrollo de proyectos de minería de datos, CRISP-DM. Adicionalmente, se emplearon diseños de comprobación para los algoritmos, con el fin de comprobar la validez del modelo de estimación basado en algoritmos de aprendizaje automático; es decir, el modelo de estimación fue evaluado a partir de un diseño de comprobación donde se definen, para cada uno de los algoritmos, los parámetros iniciales de operación, las configuraciones de las diferentes pruebas, y las métricas usadas para evaluar su desempeño. RESULTADOS Los resultados más importantes alcanzados son los siguientes: un mapa estratégico del estado de la ciencia en el aprovisionamiento de la QoE para servicios OTT, una conceptualización de los perfiles del modelo de correlación, un modelo matemático para la valoración de la QoE de acuerdo con el comportamiento de consumo de los usuarios, un conjunto de datos de tráfico etiquetado que relaciona el comportamiento de la red con la percepción de la calidad de los usuarios, y un modelo de estimación de la QoE de los usuarios a partir del comportamiento de tráfico de la red. CONCLUSIONES El modelo de correlación QoS-QoE puede ser empleado en sistemas gestión de la QoE donde se requiere por parte de la Telco un diagnóstico y monitorización más objetiva de la percepción de la calidad del servicio por parte de sus usuarios dentro su red de aprovisionamiento. De igual manera, el empleo de parámetros adicionales de contexto de usuario enriquecería los sistemas de gestión de la QoE en el aprovisionamiento de servicios OTT.BACKGROUND Quality of Experience (QoE) provisioning requires robust QoE-centric network and application management on Telco network for providing internet services. Indeed, traffic growth over Telco network demands resource allocation for service well performance. Particularly, Quality of Service (QoS) configuration offered by network provider operational domain becomes a key component for traffic control in a proper manner. Hence, the quality of services perceived can be managed within a tolerance threshold according to telecom operator policies. Therefore, a QoS-QoE correlational model for internet services provisioning over the telecom operator infrastructure is required. AIMS The doctoral thesis is focused on propose a correlation QoS-QoE model for provisioning telecommunications services in OTT-Telco context. To this end, five goals must be accomplishing. () To characterize QoS parameters that more impact have on OTT services performance. () To determinate QoE assumptions, features, parameters, and metrics for OTT service provisioning. () To establish the assumptions and restrictions for providing a well QoS-QoE relation in the telecom operator. () To develop an estimation model for QoE based on QoS factors in the OTT services provisioning. () To evaluate the correlation QoS-QoE model. METHODS To accomplish the aims, a model with a Conceptual and Operational macro-component was structured. The Conceptual macro-component is based on the principles for building conceptual frameworks by Jabareen, and an Operational macro-component aligned with data mining project development phases, CRISP-DM. Furthermore, test bed design was structured to validate the estimation model base on machine learning algorithms; namely, algorithms initial parameters, some tests setup, and regression metrics were determined on a test bed for validate the performance of the estimation model proposed RESULTS The most relevant results achieved are the following: a strategic science map in the QoE provisioning for OTT services, three conceptual profiles as part of the correlation QoS-QoE model, a mathematical model for QoE assessment according to user consumption behavior, a label traffic dataset that relates the traffic network with quality of services perception, and estimation QoE model for users based on traffic flows. CONCLUSIONS The QoS-QoE correlational model can be applied in QoE-Driven application and network management in which an objective controlling and monitoring of quality of services perception by users is required. Moreover, additional user context parameters could be taking account for improving the QoE management systems in OTT services provisioning.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: Jesús García Herrero.- Secretario: José Armando Ordóñez Córdoba.- Vocal: Juan Carlos Cuéllar Quiñóne

    Air Traffic Management Abbreviation Compendium

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    As in all fields of work, an unmanageable number of abbreviations are used today in aviation for terms, definitions, commands, standards and technical descriptions. This applies in general to the areas of aeronautical communication, navigation and surveillance, cockpit and air traffic control working positions, passenger and cargo transport, and all other areas of flight planning, organization and guidance. In addition, many abbreviations are used more than once or have different meanings in different languages. In order to obtain an overview of the most common abbreviations used in air traffic management, organizations like EUROCONTROL, FAA, DWD and DLR have published lists of abbreviations in the past, which have also been enclosed in this document. In addition, abbreviations from some larger international projects related to aviation have been included to provide users with a directory as complete as possible. This means that the second edition of the Air Traffic Management Abbreviation Compendium includes now around 16,500 abbreviations and acronyms from the field of aviation

    Video Conference as a tool for Higher Education

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    The book describes the activities of the consortium member institutions in the framework of the TEMPUS IV Joint Project ViCES - Video Conferencing Educational Services (144650-TEMPUS-2008-IT-JPGR). In order to provide the basis for the development of a distance learning environment based on video conferencing systems and develop a blended learning courses methodology, the TEMPUS Project VICES (2009-2012) was launched in 2009. This publication collects the conclusion of the project and it reports the main outcomes together with the approach followed by the different partners towards the achievement of the project's goal. The book includes several contributions focussed on specific topics related to videoconferencing services, namely how to enable such services in educational contexts so that, the installation and deployment of videoconferencing systems could be conceived an integral part of virtual open campuses

    Dynamic Quality-of-Service Management Under Software-Defined Networking Architectures

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    The Internet is facing new challenges emerging from new trends in Information and Communication Technologies (ICT) for example, cloud services, Big Data, increased mobile usage etc. Traditional IP networks rely in two design principles that, despite serving as an effective solution in the last decades, have become deprecated and not well fit for the new challenges. First, the control and data plane are tightly embedded in the networking devices and second, the structure is highly decentralized with no centralized point of management. This static and rigid architecture leaves no space for innovation with a consequence lack of scalability. Also, it leads to high management and operation costs. The SDN paradigm provides a more dynamic, manageable, cost-effective and adaptable architecture that is ready for the dynamic nature of today's applications. The goal of this thesis is a novel SDN-enabled solution that provides dynamic Quality of Service management for real-time and multimedia applications. This solution will be tested and implemented over a real, not-simulated testbed, composed by OpenFlow-enabled devices, the ONOS SDN controller and client terminals that produced/consume data streams. Furthermore, it is also expected to characterize and evaluate the benefits of the SDN-based solution against a traditional usage of the network (non-SDN)

    Telecommunications Networks

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    This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

    Mobile Ad Hoc Networks

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    Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms
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