On the Performance Evaluation of High-Speed Transport Protocols

As high-speed networks with large bandwidth delay products (BDP) become more common, high-speed transport protocols must be developed that perform well in these contexts. TCP has limitations in high BDP networks. A number of high-speed TCP proposals have emerged, including BIC TCP, High Speed TCP, and H-TCP. XCP is an intraprotocol communication mechanism that promises even greater performance by providing explicit feedback from routers about congestion. It requires changes to routers and end hosts, though, whereas the other experimental protocols only require changes to an end host. We evaluated the performance ofXCP against BIC TCP, High Speed TCP, H-TCP, and . NewReno TCP. We found that in a controlled environment, XCP gave much better performance than the other TCPs. XCP was sensitive to misconfiguration and environmental factors, though, and was more difficult to deploy. More work is required to make XCP more stable. The other TCPs did not perform better than NewReno TCP but show promise, as most performed almost as well as NewReno TCP

Challenges on the way of implementing TCP over 5G networks

5G cellular communication, especially with its hugely available bandwidth provided by millimeter-wave, is a promising technology to fulfill the coming high demand for vast data rates. These networks can support new use cases such as Vehicle to Vehicle and augmented reality due to its novel features such as network slicing along with the mmWave multi-gigabit-per-second data rate. Nevertheless, 5G cellular networks suffer from some shortcomings, especially in high frequencies because of the intermittent nature of channels when the frequency rises. Non-line of sight state, is one of the significant issues that the new generation encounters. This drawback is because of the intense susceptibility of higher frequencies to blockage caused by obstacles and misalignment. This unique characteristic can impair the performance of the reliable transport layer widely deployed protocol, TCP, in attaining high throughput and low latency throughout a fair network. As a result, the protocol needs to adjust the congestion window size based on the current situation of the network. However, TCP is not able to adjust its congestion window efficiently, and it leads to throughput degradation of the protocol. This paper presents a comprehensive analysis of reliable end-to-end communications in 5G networks. It provides the analysis of the effects of TCP in 5G mmWave networks, the discussion of TCP mechanisms and parameters involved in the performance over 5G networks, and a survey of current challenges, solutions, and proposals. Finally, a feasibility analysis proposal of machine learning-based approaches to improve reliable end-to-end communications in 5G networks is presented.This work was supported by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya under Grant 2017 SGR 376.Peer ReviewedPostprint (published version

Congestion Prediction in Internet of Things Network using Temporal Convolutional Network A Centralized Approach

The unprecedented ballooning of network traffic flow, specifically, Internet of Things (IoT) network traffic, has big stressed of congestion on todays Internet. Non-recurring network traffic flow may be caused by temporary disruptions, such as packet drop, poor quality of services, delay, etc. Hence, the network traffic flow estimation is important in IoT networks to predict congestion. As the data in IoT networks is collected from a large number of diversified devices which have unlike format of data and also manifest complex correlations, so the generated data is heterogeneous and nonlinear in nature. Conventional machine learning approaches unable to deal with nonlinear datasets and suffer from misclassification of real network traffic due to overfitting. Therefore, it also becomes really hard for conventional machine learning tools like shallow neural networks to predict the congestion accurately. Accuracy of congestion prediction algorithms play an important role to control the congestion by regulating the send rate of the source. Various deeplearning methods (LSTM, CNN, GRU, etc.) are considered in designing network traffic flow predictors, which have shown promising results. In this work, we propose a novel congestion predictor for IoT, that uses Temporal Convolutional Network (TCN). Furthermore, we use Taguchi method to optimize the TCN model that reduces the number of runs of the experiments. We compare TCN with other four deep learning-based models concerning Mean Absolute Error (MAE) and Mean Relative Error (MRE). The experimental results show that TCN based deep learning framework achieves improved performance with 95.52% accuracy in predicting network congestion. Further, we design the Home IoT network testbed to capture the real network traffic flows as no standard dataset is available

Implementation and Analysis of Communication Protocols in Internet of Things

Internet of Things (IoT) is the future of all the present-day devices around the globe. Giving them internet connectivity makes IoT the next frontier of technology. Possibilities are limitless as the devices communicate and interact with each other which make it even more interesting for the global markets. For example, Rolls-Royce announced that it would use the Microsoft Azure IoT suite and also the Intelligence suite of Cortana to keep track of the fuel usage, for performance analysis, to optimize the fly routes etc. which improves the airline efficiency. The devices must communicate with each other, the data from these devices must be collected by the servers, and the data is then analyzed or provided to the people. For all this to happen, there is a need for efficient protocols to ensure that the communication is secure and to avoid loss of data. This research is about the implementation and analysis of various protocols that can be used for the communication in IoT. Various protocols with various capabilities are required for different environments. The internet today supports hundreds of protocols from which choosing the best would be a great challenge. But each protocol is different in its own way when we have the specifics like security, reliability, range of communication etc. This research emphasizes on the best available protocols and the environments that suit them the most. It provides an implementation of some of the protocols and analyzes the protocols according to the results obtained. The data collected from the sensors/devices through a protocol is also subject to predictive analysis which improves the scope of the project to performing data analysis on the data collected through IoT

Making broadband access networks transparent to researchers, developers, and users

Broadband networks are used by hundreds of millions of users to connect to the Internet today. However, most ISPs are hesitant to reveal details about their network deployments,and as a result the characteristics of broadband networks are often not known to users,developers, and researchers. In this thesis, we make progress towards mitigating this lack of transparency in broadband access networks in two ways. First, using novel measurement tools we performed the first large-scale study of thecharacteristics of broadband networks. We found that broadband networks have very different characteristics than academic networks. We also developed Glasnost, a system that enables users to test their Internet access links for traffic differentiation. Glasnost has been used by more than 350,000 users worldwide and allowed us to study ISPs' traffic management practices. We found that ISPs increasingly throttle or even block traffic from popular applications such as BitTorrent. Second, we developed two new approaches to enable realistic evaluation of networked systems in broadband networks. We developed Monarch, a tool that enables researchers to study and compare the performance of new and existing transport protocols at large scale in broadband environments. Furthermore, we designed SatelliteLab, a novel testbed that can easily add arbitrary end nodes, including broadband nodes and even smartphones, to existing testbeds like PlanetLab.Breitbandanschlüsse werden heute von hunderten Millionen Nutzern als Internetzugang verwendet. Jedoch geben die meisten ISPs nur ungern über Details ihrer Netze Auskunft und infolgedessen sind Nutzern, Anwendungsentwicklern und Forschern oft deren Eigenheiten nicht bekannt. Ziel dieser Dissertation ist es daher Breitbandnetze transparenter zu machen. Mit Hilfe neuartiger Messwerkzeuge konnte ich die erste groß angelegte Studie über die Besonderheiten von Breitbandnetzen durchführen. Dabei stellte sich heraus, dass Breitbandnetze und Forschungsnetze sehr unterschiedlich sind. Mit Glasnost habe ich ein System entwickelt, das mehr als 350.000 Nutzern weltweit ermöglichte ihren Internetanschluss auf den Einsatz von Verkehrsmanagement zu testen. Ich konnte dabei zeigen, dass ISPs zunehmend BitTorrent Verkehr drosseln oder gar blockieren. Meine Studien zeigten dar überhinaus, dass existierende Verfahren zum Testen von Internetsystemen nicht die typischen Eigenschaften von Breitbandnetzen berücksichtigen. Ich ging dieses Problem auf zwei Arten an: Zum einen entwickelte ich Monarch, ein Werkzeug mit dem das Verhalten von Transport-Protokollen über eine große Anzahl von Breitbandanschlüssen untersucht und verglichen werden kann. Zum anderen habe ich SatelliteLab entworfen, eine neuartige Testumgebung, die, anders als zuvor, beliebige Internetknoten, einschließlich Breitbandknoten und sogar Handys, in bestehende Testumgebungen wie PlanetLab einbinden kann

Moving toward the intra-protocol de-ossification of TCP in mobile networks: Start-up and mobility

182 p.El uso de las redes móviles de banda ancha ha aumentado significativamente los últimos años y se espera un crecimiento aún mayor con la inclusión de las futuras capacidades 5G. 5G proporcionará unas velocidades de transmisión y reducidos retardos nunca antes vistos. Sin embargo, la posibilidad de alcanzar las mencionadas cuotas está limitada por la gestión y rendimiento de los protocolos de transporte. A este respecto, TCP sigue siendo el protocolo de transporte imperante y sus diferentes algoritmos de control de congestión (CCA) los responsables finales del rendimiento obtenido. Mientras que originalmente los distintos CCAs han sido implementados para hacer frente a diferentes casos de uso en redes fijas, ninguno de los CCAs ha sido diseñado para poder gestionar la variabilidad de throughput y retardos de diferentes condiciones de red redes móviles de una manera fácilmente implantable. Dado que el análisis de TCP sobre redes móviles es complejo debido a los múltiples factores de impacto, nuestro trabajo se centra en dos casos de uso generalizados que resultan significativos en cuanto a afección del rendimiento: movimiento de los usuarios como representación de la característica principal de las redes móviles frente a las redes fijas y el rendimiento de la fase de Start-up de TCP debido a la presencia mayoritaria de flujos cortos en Internet. Diferentes trabajos han sugerido la importancia de una mayor flexibilidad en la capa de transporte, creando servicios de transporte sobre TCP o UDP. Sin embargo, estas propuestas han encontrado limitaciones relativas a las dependencias arquitecturales de los protocolos utilizados como sustrato (p.ej. imposibilidad de cambiar la configuración de la capa de transporte una vez la transmisión a comenzado), experimentando una capa de transporte "osificada". Esta tesis surge como respuesta a fin de abordar la citada limitación y demostrando que existen posibilidades de mejora dentro de la familia de TCP (intra-protocolar), proponiendo un marco para solventar parcialmente la restricción a través de la selección dinámica del CCA más apropiado. Para ello, se evalúan y seleccionan los mayores puntos de impacto en el rendimiento de los casos de uso seleccionados en despliegues de red 4G y en despliegues de baja latencia que emulan las potenciales latencias en las futuras capacidades 5G. Estos puntos de impacto sirven como heurísticas para decidir el CCA más apropiado en el propuesto marco. Por último, se valida la propuesta en entornos de movilidad con dos posibilidades de selección: al comienzo de la transmisión (limitada flexibilidad de la capa de transporte) y dinámicamente durante la transmisión (con una capa de transporte flexible). Se concluye que la propuesta puede acarrear importantes mejoras de rendimiento al seleccionar el CCA más apropiado teniendo en cuenta la situación de red y los requerimientos de la capa de aplicación

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

Advanced SDN-Based QoS and Security Solutions for Heterogeneous Networks

This thesis tries to study how SDN can be employed in order to support Quality of Service and how the support of this functionality is fundamental for today networks. Considering, not only the present networks, but also the next generation ones, the importance of the SDN paradigm become manifest as the use of satellite networks, which can be useful considering their broadcasting capabilities. For these reasons, this research focuses its attention on satellite - terrestrial networks and in particular on the use of SDN inside this environment. An important fact to be taken into account is that the growing of the information technologies has pave the way for new possible threats. This research study tries to cover also this problem considering how SDN can be employed for the detection of past and future malware inside networks