Accelerated V2X provisioning with Extensible Processor Platform

With the burgeoning Vehicle-to-Everything (V2X) communication, security and privacy concerns are paramount. Such concerns are usually mitigated by combining cryptographic mechanisms with suitable key management architecture. However, cryptographic operations may be quite resource-intensive, placing a considerable burden on the vehicle’s V2X computing unit. To assuage this issue, it is reasonable to use hardware acceleration for common cryptographic primitives, such as block ciphers, digital signature schemes, and key exchange protocols. In this scenario, custom extension instructions can be a plausible option, since they achieve fine-tune hardware acceleration with a low to moderate logic overhead, while also reducing code size. In this article, we apply this method along with dual-data memory banks for the hardware acceleration of the PRESENT block cipher, as well as for the $F_{2^{255}-19}$ finite field arithmetic employed in cryptographic primitives based on Curve25519 (e.g., EdDSA and X25519). As a result, when compared with a state-of-the-art software-optimized implementation, the performance of PRESENT is improved by a factor of 17 to 34 and code size is reduced by 70%, with only a 4.37% increase in FPGA logic overhead. In addition, we improve the performance of operations over Curve25519 by a factor of ~2.5 when compared to an Assembly implementation on a comparable processor, with moderate logic overhead (namely, 9.1%). Finally, we achieve significant performance gains in the V2X provisioning process by leveraging our hardware-accelerated cryptographic primitive

Implementação de serviços em ambientes multi-access edge computing

Driven by the visions of the 5th Generation of Mobile Networks (5G), and with an increasing acceptance of software-based network technologies, such as Network Function Virtualization (NFV) and Software Defined Networks (SDN), a transformation in network infrastructure is presently taking place, along with different requirements in terms of how networks are managed and deployed. One of the significantly changes is a shift in the cloud computing paradigm, moving from a centralized cloud computing towards the edge of the network. This new environment, providing a cloud computing platform at the edge of the network, is referred to as Multi-Acess Edge Computing (MEC). The main feature of MEC is to provide mobile computing, network control and storage to the network edges, enabling computation-intensive and latency-critical applications targeting resource-limited mobile devices. In this thesis a MEC architecture solution is provided, capable of supporting heterogeneous access networks, to assist as a platform for service deployment. Several MEC use case scenarios are evaluated on the proposed scheme, in order to attest the advantages of a MEC deployment. Results show that the proposed environment is significantly faster on performing compute-intensive applications, mainly due to lower end-to-end latency, when compared to traditional centralized cloud servers, translating into energy saving, and reduced backhaul traffic.Impulsionados pelas visões da quinta geração de redes móveis, e com uma crescente aceitação das tecnologias de redes baseadas em software, tais como funções de redes virtualizadas (NFV) e redes definidas por software (SDN), encontramo-nos perante uma transformação na infraestrutura nas redes de telecomunicações, assim como no modo como estas são geridas e implementadas. Uma das alterações mais significativas é a mudança no paradigma de computação na cloud, passando de uma implementação centralizada para uma ramificada na direção das extremidades da rede. Este novo ambiente, que possibilita uma plataforma de computação na extremidade da rede, é denominado de Multi-Access Edge Computing (MEC). A principal característica do MEC é fornecer computação móvel, armazenamento e recursos de rede na extremidade da rede, permitindo que terminais móveis com recursos limitados tenham acesso a aplicações exigentes em termos de latência e computação. Na presente tese, é apresentada uma solução de arquitetura MEC, que suporta ligações a redes de acesso heterogéneas, servindo de plataforma para a implementação de serviços. Alguns cenários MEC foram aplicados e avaliados na plataforma proposta, de forma a demonstrar as vantagens da implementação MEC. Os resultados demonstram que a plataforma proposta é significativamente mais rápida na execução computação intensiva, maioritariamente devido à baixa latência, quando comparado com os tradicionais datacenters centralizados, resultando numa poupança de energia e redução de tráfego no backhaul.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing

Demystifying Internet of Things Security

Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

View on 5G Architecture: Version 1.0

The current white paper focuses on the produced results after one year research mainly from 16 projects working on the abovementioned domains. During several months, representatives from these projects have worked together to identify the key findings of their projects and capture the commonalities and also the different approaches and trends. Also they have worked to determine the challenges that remain to be overcome so as to meet the 5G requirements. The goal of 5G Architecture Working Group is to use the results captured in this white paper to assist the participating projects achieve a common reference framework. The work of this working group will continue during the following year so as to capture the latest results to be produced by the projects and further elaborate this reference framework. The 5G networks will be built around people and things and will natively meet the requirements of three groups of use cases: • Massive broadband (xMBB) that delivers gigabytes of bandwidth on demand • Massive machine-type communication (mMTC) that connects billions of sensors and machines • Critical machine-type communication (uMTC) that allows immediate feedback with high reliability and enables for example remote control over robots and autonomous driving. The demand for mobile broadband will continue to increase in the next years, largely driven by the need to deliver ultra-high definition video. However, 5G networks will also be the platform enabling growth in many industries, ranging from the IT industry to the automotive, manufacturing industries entertainment, etc. 5G will enable new applications like for example autonomous driving, remote control of robots and tactile applications, but these also bring a lot of challenges to the network. Some of these are related to provide low latency in the order of few milliseconds and high reliability compared to fixed lines. But the biggest challenge for 5G networks will be that the services to cater for a diverse set of services and their requirements. To achieve this, the goal for 5G networks will be to improve the flexibility in the architecture. The white paper is organized as follows. In section 2 we discuss the key business and technical requirements that drive the evolution of 4G networks into the 5G. In section 3 we provide the key points of the overall 5G architecture where as in section 4 we elaborate on the functional architecture. Different issues related to the physical deployment in the access, metro and core networks of the 5G network are discussed in section 5 while in section 6 we present software network enablers that are expected to play a significant role in the future networks. Section 7 presents potential impacts on standardization and section 8 concludes the white paper

Actas de las XIV Jornadas de Ingeniería Telemática (JITEL 2019) Zaragoza (España) 22-24 de octubre de 2019

En esta ocasión, es la ciudad de Zaragoza la encargada de servir de anfitriona a las XIV Jornadas de Ingeniería Telemática (JITEL 2019), que se celebrarán del 22 al 24 de octubre de 2019. Las Jornadas de Ingeniería Telemática (JITEL), organizadas por la Asociación de Telemática (ATEL), constituyen un foro propicio de reunión, debate y divulgación para los grupos que imparten docencia e investigan en temas relacionados con las redes y los servicios telemáticos. Con la organización de este evento se pretende fomentar, por un lado el intercambio de experiencias y resultados, además de la comunicación y cooperación entre los grupos de investigación que trabajan en temas relacionados con la telemática. En paralelo a las tradicionales sesiones que caracterizan los congresos científicos, se desea potenciar actividades más abiertas, que estimulen el intercambio de ideas entre los investigadores experimentados y los noveles, así como la creación de vínculos y puntos de encuentro entre los diferentes grupos o equipos de investigación. Para ello, además de invitar a personas relevantes en los campos correspondientes, se van a incluir sesiones de presentación y debate de las líneas y proyectos activos de los mencionados equipos

Modern computing: Vision and challenges

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress