Distributed Access Control with Blockchain

The specification and enforcement of network-wide policies in a single administrative domain is common in today's networks and considered as already resolved. However, this is not the case for multi-administrative domains, e.g. among different enterprises. In such situation, new problems arise that challenge classical solutions such as PKIs, which suffer from scalability and granularity concerns. In this paper, we present an extension to Group-Based Policy -- a widely used network policy language -- for the aforementioned scenario. To do so, we take advantage of a permissioned blockchain implementation (Hyperledger Fabric) to distribute access control policies in a secure and auditable manner, preserving at the same time the independence of each organization. Network administrators specify polices that are rendered into blockchain transactions. A LISP control plane (RFC 6830) allows routers performing the access control to query the blockchain for authorizations. We have implemented an end-to-end experimental prototype and evaluated it in terms of scalability and network latency.Comment: 7 pages, 9 figures, 2 table

Programari per a la personalització de motors de TA. Anàlisi de productes

L'objectiu d'aquest Treball de Fi de Màster és analitzar programari que permet la personalització de motors de TA. Amb aquest propòsit s'han escollit 6 eines diferents (Machine Translation Training Tool, ModernMT, MTradumàtica, LetsMT, KantanMT i Microsoft Translation Hub) i s'ha investigat la seva instal·lació i el seu entrenament. A més, es proporciona una explicació teòrica sobre els sistemes de TA, la qualitat en TA i el seu estat de la qüestió. De la mateixa manera, es descriuen amb precisió els recursos que s'han utilitzat durant el treball, les característiques principals de les eines, la creació dels dos corpus i la instal·lació i l'entrenament del programari. Amb els motors ja entrenats s'ha preparat un resum de les característiques més importants de cada eina i una anàlisi de la qualitat de la TA. A banda d'aquests resultats, aquest treball subratlla els mètodes relatius a la instal·lació i a l'entrenament dels programes.El objetivo de este Trabajo de Fin de Máster es analizar software que permite la personalización de motores de TA. Con este propósito se han escogido 6 herramientas distintas (Machine Translation Training Tool, ModernMT, MTradumàtica, LetsMT, KantanMT y Microsoft Translation Hub) y se ha indagado acerca de su instalación y de su entrenamiento. Además, se han creado dos corpus (chino-catalán y francés-catalán) para entrenar los motores de estos programes con combinaciones lingüísti-cas concretas. Así, se proporciona una explicación teórica acerca de los sistemas de TA, de la calidad en TA y de su estado de la cuestión. De la misma manera, se describen con precisión los recursos que se han utilizado a lo largo de este trabajo, las características principales de las herramientas, la crea-ción de los dos corpus y la instalación y el entrenamiento del software. Con los motores ya entrenados se ha preparado un resumen de las características más relevantes de cada herramienta y un análisis de la calidad de la TA. A parte de estos resultados, este trabajo subraya los métodos relativos a la ins-talación y al entrenamiento de los programas.The aim of this Master's Degree Dissertation is analyzing software that allows engine customization of Machine Translation. With this purpose 6 different tools (Machine Translation Training Tool, Mo-dernMT, MTradumàtica, LetsMT, KantanMT and Microsoft Translation Hub) have been chosen and their installation and their engine training have been explored. Moreover, two corpus (chinese-catalan and french-catalan) have been created in order to train the engines with specific linguistic combina-tions. A theoretical explanation about MT systems, quality in MT and its state-of-the-art is provided. Likewise, the resources used during this dissertation, the tools' main features, every single step of the creation of both corpus and the installation and the training of the software is described. Once the engines have been trained, a summary of the most significant features of each tool and the analysis of the quality of the MT are given. Apart from these results, this dissertation highlights the methods of the installation and the training

RouteNet-Fermi: Network Modeling with Graph Neural Networks

Network models are an essential block of modern networks. For example, they are widely used in network planning and optimization. However, as networks increase in scale and complexity, some models present limitations, such as the assumption of Markovian traffic in queuing theory models, or the high computational cost of network simulators. Recent advances in machine learning, such as Graph Neural Networks (GNN), are enabling a new generation of network models that are data-driven and can learn complex non-linear behaviors. In this paper, we present RouteNet-Fermi, a custom GNN model that shares the same goals as Queuing Theory, while being considerably more accurate in the presence of realistic traffic models. The proposed model predicts accurately the delay, jitter, and packet loss of a network. We have tested RouteNet-Fermi in networks of increasing size (up to 300 nodes), including samples with mixed traffic profiles -- e.g., with complex non-Markovian models -- and arbitrary routing and queue scheduling configurations. Our experimental results show that RouteNet-Fermi achieves similar accuracy as computationally-expensive packet-level simulators and scales accurately to larger networks. Our model produces delay estimates with a mean relative error of 6.24% when applied to a test dataset of 1,000 samples, including network topologies one order of magnitude larger than those seen during training. Finally, we have also evaluated RouteNet-Fermi with measurements from a physical testbed and packet traces from a real-life network.Comment: This paper has been accepted for publication at IEEE/ACM Transactions on Networking 2023 (DOI: 10.1109/TNET.2023.3269983). \copyright 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other use

La evolución de la situación de la enseñanza del chino en Catalunya a lo largo de los últimos 20 años

En mi trabajo titulado 'La evolución de la situación de la enseñanza del chino en Catalunya a lo largo de los últimos 20 años' exploro la situación del chino en Cataluña a lo largo de estas tres últimas décadas. El chino ha tenido una trayectoria notable, pues se ha pasado de conocer muy poco a conocer mucho sobre China y la lengua china. En el trabajo, hago una recopilación de hechos históricos e informaciones sobre la enseñanza de la lengua china en Cataluña, de sus centros docentes y del perfil de sus usuarios en los ámbitos académicos. En las diferentes modalidades de escuelas de chino, nos encontramos con diversa tipología de estudiantes, de material docente, de perfiles de profesores de chino y de diferentes usos de la lengua china en un contexto europeo. Al final, expongo mis reflexiones y conclusiones sobre el estudio de campo realizad

Mechanical cough augmentation techniques in amyotrophic lateral sclerosis/motor neuron disease

© 2016 The Cochrane Collaboration.This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: To assess the effects of mechanical insufflator/exsufflator (MI-E) and the breath-stacking technique for reducing morbidity and mortality and enhancing quality of life in people with amyotrophic lateral sclerosis (ALS)/motor neuron disease (MND)

Network Digital Twin: Context, Enabling Technologies and Opportunities

The proliferation of emergent network applications (e.g., telesurgery, metaverse) is increasing the difficulty of managing modern communication networks. These applications entail stringent network requirements (e.g., ultra-low deterministic latency), which hinders network operators to manage their resources efficiently. In this article, we introduce the network digital twin (NDT), a renovated concept of classical network modeling tools whose goal is to build accurate data-driven network models that can operate in real-time. We describe the general architecture of the NDT and argue that modern machine learning (ML) technologies enable building some of its core components. Then, we present a case study that leverages a ML-based NDT for network performance evaluation and apply it to routing optimization in a QoS-aware use case. Lastly, we describe some key open challenges and research opportunities yet to be explored to achieve effective deployment of NDTs in real-world networks.Comment: 7 pages, 4 figures. arXiv admin note: text overlap with arXiv:2201.0114