5G-MEC Testbeds for V2X Applications

Fifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low latency and high computational capabilities at the network’s edge. To meet these requirements, ETSI standardized Multi-access Edge Computing (MEC), which provides cloud computing capabilities and addresses the need for low latency. This paper presents a generalized overview for implementing a 5G-MEC testbed for Vehicle-to-Everything (V2X) applications, as well as the analysis of some important testbeds and state-of-the-art implementations based on their deployment scenario, 5G use cases, and open source accessibility. The complexity of using the testbeds is also discussed, and the challenges researchers may face while replicating and deploying them are highlighted. Finally, the paper summarizes the tools used to build the testbeds and addresses open issues related to implementing the testbeds.publishedVersio

A Comprehensive Review on Time Sensitive Networks with a Special Focus on Its Applicability to Industrial Smart and Distributed Measurement Systems

The groundbreaking transformations triggered by the Industry 4.0 paradigm have dramati-cally reshaped the requirements for control and communication systems within the factory systems of the future. The aforementioned technological revolution strongly affects industrial smart and distributed measurement systems as well, pointing to ever more integrated and intelligent equipment devoted to derive accurate measurements. Moreover, as factory automation uses ever wider and complex smart distributed measurement systems, the well-known Internet of Things (IoT) paradigm finds its viability also in the industrial context, namely Industrial IoT (IIoT). In this context, communication networks and protocols play a key role, directly impacting on the measurement accuracy, causality, reliability and safety. The requirements coming both from Industry 4.0 and the IIoT, such as the coexistence of time-sensitive and best effort traffic, the need for enhanced horizontal and vertical integration, and interoperability between Information Technology (IT) and Operational Technology (OT), fostered the development of enhanced communication subsystems. Indeed, established tech-nologies, such as Ethernet and Wi-Fi, widespread in the consumer and office fields, are intrinsically non-deterministic and unable to support critical traffic. In the last years, the IEEE 802.1 Working Group defined an extensive set of standards, comprehensively known as Time Sensitive Networking (TSN), aiming at reshaping the Ethernet standard to support for time-, mission-and safety-critical traffic. In this paper, a comprehensive overview of the TSN Working Group standardization activity is provided, while contextualizing TSN within the complex existing industrial technological panorama, particularly focusing on industrial distributed measurement systems. In particular, this paper has to be considered a technical review of the most important features of TSN, while underlining its applicability to the measurement field. Furthermore, the adoption of TSN within the Wi-Fi technology is addressed in the last part of the survey, since wireless communication represents an appealing opportunity in the industrial measurement context. In this respect, a test case is presented, to point out the need for wirelessly connected sensors networks. In particular, by reviewing some literature contributions it has been possible to show how wireless technologies offer the flexibility necessary to support advanced mobile IIoT applications

Ruuhkan- ja jononhallinta tiedonsiirron alkuvaiheessa

Transmission Control Protocol (TCP) has served as the workhorse to transmit Internet traffic for several decades already. Its built-in congestion control mechanism has proved reliable to ensure the stability of the Internet, and congestion control algorithms borrowed from TCP are being applied largely also by other transport protocols. TCP congestion control has two main phases for increasing sending rate. Slow Start is responsible for starting up a flow by seeking the sending rate the flow should use. Congestion Avoidance then takes over to manage the sending rate for flows that last long enough. In addition, the flow is booted up by sending the Initial Window of packets prior to Slow Start. There is a large difference in the magnitude of sending rate increase during Slow Start and Congestion Avoidance. Slow Start increases the sending rate exponentially, whereas with Congestion Avoidance the increase is linear. If congestion is detected, a standard TCP sender reduces the sending rate heavily. It is well known that most of the Internet flows are short. It implies that flow startup is a rather frequent phenomenon.  Also, many traffic types exhibit an ON-OFF pattern with senders remaining idle for varying periods of time. As the flow startup under Slow Start causes exponential sending rate increase, the link load is often subject to exponential load transients that escalate in a few round trips into overload, if not controlled properly. It is true especially near the network edge where traffic aggregation is limited to a few users. Traditionally much of the congestion control research has focused on behavior during Congestion Avoidance and uses large aggregates during testing. To control router load, Active Queue Management (AQM) is recommended. The state-of-the-art AQM algorithms, however, are designed with little attention to Slow Start. This thesis focuses on congestion control and AQM during the flow startup. We explore what effect the Initial Window has to competing latency-sensitive traffic during a flow startup consisting of multiple parallel flows typical to Web traffic and investigate the impact of increasing Initial Window from three to ten TCP segments. We also highlight what the shortcomings are in the state-of-the-art AQM algorithms and formulate the challenges AQM algorithms must address to properly handle flow startup and exponential load transients. These challenges include the horizon problem, RTT (round-trip time) uncertainty and rapidly changing load. None of the existing AQM algorithms are prepared to handle these challenges. Therefore we explore whether an existing AQM algorithm called Random Early Detection (RED) can be altered to control exponential load transients effectively and propose necessary changes to RED. We also propose an entirely new AQM algorithm called Predict. It is the first AQM algorithm designed primarily for handling exponential load transients. Our evaluation shows that because of shortcomings in handling exponential load transients, the state-of-the-art AQM algorithms often respond too slowly or too fast depending on the actual RTT of the traffic. In contrast, the Predict AQM algorithm performs timely congestion indication without compromising throughput or latency unnecessarily, yielding low latency over a large range of RTTs. In addition, the load estimation in Predict is designed to be fully compatible with pacing and the timely congestion indication allows relaxing the large sending rate reduction on congestion detection.Ruuhkanhallinta on yksi keskeisimpiä Internetin sujuvan dataliikenteen turvaavia toimintoja. Ilman toimivaa ruuhkanhallintaa Internet ylikuormittuisi ja tulisi käyttökelvottomaksi. TCP-protokollaa (Transmission Control Protocol) on käytetty siirtämään tietoa Internetissä jo vuosia. Sen sisäänrakennettu ruuhkanhallinta on osoittautunut tehokkaaksi estämään pitkäkestoista verkon ylikuormittumista. TCP:n keskeiset ruuhkanhallinta-algoritmit ovat hidas aloitus (Slow Start) ja ruuhkan välttely (Congestion Avoidance). Hidasta aloitusta käytetään vallitsevan verkkotilanteen salliman lähetysnopeuden selvittämiseen. Kun sopiva lähetysnopeus on saavutettu, TCP siirtyy käyttämään ruuhkan välttely -algoritmia. Hitaan aloituksen ja ruuhkan välttelyn käyttämät algoritmit eroavat merkittävästi toisistaan. Hidas aloitus kasvattaa lähetysnopeutta eksponentiaalisesti, kun taas ruuhkan välttelyn aikana lähetysnopeus kasvaa lineaarisesti. Koska Internetissä yhden tiedonsiirtoyhteyden yli siirrettävä tietomäärä on tyypillisesti vähäinen ja uusien yhteyksien tiheä avaaminen sekä lähetystauot ovat erittäin yleisiä, aiheutuu hitaan aloituksen käyttämisestä usein toistuvia kuormapiikkejä, joiden aikana kuorman kasvu verkossa on eksponentiaalista. Verkon reuna-alueella lähellä käyttäjän laitetta verkon kuorma koostuu tyypillisesti vain yhden tai muutaman käyttäjän liikenteestä, jolloin kuormatason vaihtelu on suurta ja siirtyminen matalasta kuormasta ylikuormaan tapahtuu hitaan aloituksen käyttämisen takia erittäin nopeasti. Standardinmukaisen TCP:n hidas aloitus -algoritmi edellyttää ruuhkasignaalia joltakin verkkopolun liikennettä välittävältä reitittimeltä ennen kuin hidas aloitus lopetetaan ja siirrytään ruuhkan välttely -algoritmin käyttöön. Valtaosa aiemmasta ruuhkanhallintaan kohdistuvasta tietoliikennetutkimuksesta on sivuuttanut hitaan aloituksen ja on keskittynyt huomioimaan pelkästään ruuhkan välttely -algoritmille ominaisen toiminnan. Tämä väitöstyö sen sijaan keskittyy ongelmiin, joita aiheutuu uusien yhteyksien avaamisesta ja hitaan aloituksen käyttämisestä. Tämä väitöstyö osoittaa etteivät reitittimissä toimivat jononhallinta-algoritmit (Active Queue Management), jotka säätelevät ruuhkasignaaleja, yleensä reagoi riittävän nopeasti hitaaseen aloitukseen. Siksi hidas aloitus pääsee kiihdyttämään lähetysnopeutta huomattavasti yli verkkotilanteen mukaisesti määrittyvän sopivan lähetysnopeuden. Tämä ylitys siirtyy yleensä suoraan siirtoviiveeseen kasvattaen sitä, mikä myös osoitetaan tapahtuvan hitaan aloituksen aikana nykyaikaisia jononhallinta-algoritmeja käytettäessä. Toisaalta samat algoritmit voivat reagoida myös liian nopeasti, jos kiertoviive on pitkä, koska monet algoritmit perustuvat oletettuun maksimikiertoviiveeseen (yleensä 100 millisekunttia). Tämä väitöstyö valottaa kuinka jononhallinta-algoritmin on haasteellista selvittää todellinen kuormataso tutkimalla reitittimellä olevaa jonoa. Kyse on eräänlaisesta "horisontista", joka estää näkemästä kuormaa aiheuttavia tietoliikennepaketteja muilta verkkopolun osilta. Myös pidempikestoinen kuormamittaus on haasteellista, koska reitittimellä ei yleensä ole tietoa kuinka pitkää ajanjaksoa tulisi käyttää mittauksessa. Lisäksi hitaan aloituksen aikana nopeasti muuttuva kuormataso johtaa kuormamittaustulosten vanhenemiseen ennenaikaisesti. Jotta ruuhkasignaali voitaisiin lähettää ajoissa, täytyy jononhallinta-algoritmin huomioida kaikki kolme yllämainittua haastetta. Tämän väitöstyön osana suunniteltiin Predict-niminen jononhallinta-algoritmi, joka osaa havaita hitaan aloituksen ja reagoi siihen oikeaan aikaan estäen tehokkaasti hitaasta aloituksesta johtuvan ylikuormituksen ja siitä johtuvat suuret viivepiikit. Näin ollen Predict välttää muille algoritmeille ongelmalliset reagointinopeuden sudenkuopat. Lisäksi työssä selvitettiin kuinka uusien yhteyksien avaamista tulisi hallita, jotta samanaikaisesti mahdollisesti käynnissä olevalle interaktiiviselle tiedonsiirrolle ei aiheuteta ongelmia

Special Topics in Information Technology

This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2019-20 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

Esquema de controlo para redes multicast baseadas com classes

Doutoramento em Engenharia ElectrotécnicaThe expectations of citizens from the Information Technologies (ITs) are increasing as the ITs have become integral part of our society, serving all kinds of activities whether professional, leisure, safety-critical applications or business. Hence, the limitations of the traditional network designs to provide innovative and enhanced services and applications motivated a consensus to integrate all services over packet switching infrastructures, using the Internet Protocol, so as to leverage flexible control and economical benefits in the Next Generation Networks (NGNs). However, the Internet is not capable of treating services differently while each service has its own requirements (e.g., Quality of Service - QoS). Therefore, the need for more evolved forms of communications has driven to radical changes of architectural and layering designs which demand appropriate solutions for service admission and network resources control. This Thesis addresses QoS and network control issues, aiming to improve overall control performance in current and future networks which classify services into classes. The Thesis is divided into three parts. In the first part, we propose two resource over-reservation algorithms, a Class-based bandwidth Over-Reservation (COR) and an Enhanced COR (ECOR). The over-reservation means reserving more bandwidth than a Class of Service (CoS) needs, so the QoS reservation signalling rate is reduced. COR and ECOR allow for dynamically defining over-reservation parameters for CoSs based on network interfaces resource conditions; they aim to reduce QoS signalling and related overhead without incurring CoS starvation or waste of bandwidth. ECOR differs from COR by allowing for optimizing control overhead minimization. Further, we propose a centralized control mechanism called Advanced Centralization Architecture (ACA), that uses a single state-full Control Decision Point (CDP) which maintains a good view of its underlying network topology and the related links resource statistics on real-time basis to control the overall network. It is very important to mention that, in this Thesis, we use multicast trees as the basis for session transport, not only for group communication purposes, but mainly to pin packets of a session mapped to a tree to follow the desired tree. Our simulation results prove a drastic reduction of QoS control signalling and the related overhead without QoS violation or waste of resources. Besides, we provide a generic-purpose analytical model to assess the impact of various parameters (e.g., link capacity, session dynamics, etc.) that generally challenge resource overprovisioning control. In the second part of this Thesis, we propose a decentralization control mechanism called Advanced Class-based resource OverpRovisioning (ACOR), that aims to achieve better scalability than the ACA approach. ACOR enables multiple CDPs, distributed at network edge, to cooperate and exchange appropriate control data (e.g., trees and bandwidth usage information) such that each CDP is able to maintain a good knowledge of the network topology and the related links resource statistics on real-time basis. From scalability perspective, ACOR cooperation is selective, meaning that control information is exchanged dynamically among only the CDPs which are concerned (correlated). Moreover, the synchronization is carried out through our proposed concept of Virtual Over-Provisioned Resource (VOPR), which is a share of over-reservations of each interface to each tree that uses the interface. Thus, each CDP can process several session requests over a tree without requiring synchronization between the correlated CDPs as long as the VOPR of the tree is not exhausted. Analytical and simulation results demonstrate that aggregate over-reservation control in decentralized scenarios keep low signalling without QoS violations or waste of resources. We also introduced a control signalling protocol called ACOR Protocol (ACOR-P) to support the centralization and decentralization designs in this Thesis. Further, we propose an Extended ACOR (E-ACOR) which aggregates the VOPR of all trees that originate at the same CDP, and more session requests can be processed without synchronization when compared with ACOR. In addition, E-ACOR introduces a mechanism to efficiently track network congestion information to prevent unnecessary synchronization during congestion time when VOPRs would exhaust upon every session request. The performance evaluation through analytical and simulation results proves the superiority of E-ACOR in minimizing overall control signalling overhead while keeping all advantages of ACOR, that is, without incurring QoS violations or waste of resources. The last part of this Thesis includes the Survivable ACOR (SACOR) proposal to support stable operations of the QoS and network control mechanisms in case of failures and recoveries (e.g., of links and nodes). The performance results show flexible survivability characterized by fast convergence time and differentiation of traffic re-routing under efficient resource utilization i.e. without wasting bandwidth. In summary, the QoS and architectural control mechanisms proposed in this Thesis provide efficient and scalable support for network control key sub-systems (e.g., QoS and resource control, traffic engineering, multicasting, etc.), and thus allow for optimizing network overall control performance.À medida que as Tecnologias de Informação (TIs) se tornaram parte integrante da nossa sociedade, a expectativa dos cidadãos relativamente ao uso desses serviços também demonstrou um aumento, seja no âmbito das atividades profissionais, de lazer, aplicações de segurança crítica ou negócios. Portanto, as limitações dos projetos de rede tradicionais quanto ao fornecimento de serviços inovadores e aplicações avançadas motivaram um consenso quanto à integração de todos os serviços e infra-estruturas de comutação de pacotes, utilizando o IP, de modo a extrair benefícios económicos e um controlo mais flexível nas Redes de Nova Geração (RNG). Entretanto, tendo em vista que a Internet não apresenta capacidade de diferenciação de serviços, e sabendo que cada serviço apresenta as suas necessidades próprias, como por exemplo, a Qualidade de Serviço - QoS, a necessidade de formas mais evoluídas de comunicação tem-se tornado cada vez mais visível, levando a mudanças radicais na arquitectura das redes, que exigem soluções adequadas para a admissão de serviços e controlo de recursos de rede. Sendo assim, este trabalho aborda questões de controlo de QoS e rede com o objetivo de melhorar o desempenho do controlo de recursos total em redes atuais e futuras, através da análise dos serviços de acordo com as suas classes de serviço. Esta Tese encontra-se dividida em três partes. Na primeira parte são propostos dois algoritmos de sobre-reserva, o Class-based bandwidth Over-Reservation (COR) e uma extensão melhorada do COR denominado de Enhanced COR (ECOR). A sobre-reserva significa a reserva de uma largura de banda maior para o serviço em questão do que uma classe de serviço (CoS) necessita e, portanto, a quantidade de sinalização para reserva de recursos é reduzida. COR e ECOR consideram uma definição dinâmica de sobre-reserva de parâmetros para CoSs com base nas condições da rede, com vista à redução da sobrecarga de sinalização em QoS sem que ocorra desperdício de largura de banda. O ECOR, por sua vez, difere do COR por permitir a otimização com minimização de controlo de overhead. Além disso, nesta Tese é proposto também um mecanismo de controlo centralizado chamado Advanced Centralization Architecture (ACA) , usando um único Ponto de Controlo de Decisão (CDP) que mantém uma visão ampla da topologia de rede e de análise dos recursos ocupados em tempo real como base de controlo para a rede global. Nesta Tese são utilizadas árvores multicast como base para o transporte de sessão, não só para fins de comunicação em grupo, mas principalmente para que os pacotes que pertençam a uma sessão que é mapeada numa determinada árvore sigam o seu caminho. Os resultados obtidos nas simulações dos mecanismos mostram uma redução significativa da sobrecarga da sinalização de controlo, sem a violação dos requisitos de QoS ou desperdício de recursos. Além disso, foi proposto um modelo analítico no sentido de avaliar o impacto provocado por diversos parâmetros (como por exemplo, a capacidade da ligação, a dinâmica das sessões, etc), no sobre-provisionamento dos recursos. Na segunda parte desta tese propôe-se um mecanismo para controlo descentralizado de recursos denominado de Advanced Class-based resource OverprRovisioning (ACOR), que permite obter uma melhor escalabilidade do que o obtido pelo ACA. O ACOR permite que os pontos de decisão e controlo da rede, os CDPs, sejam distribuídos na periferia da rede, cooperem entre si, através da troca de dados e controlo adequados (por exemplo, localização das árvores e informações sobre o uso da largura de banda), de tal forma que cada CDP seja capaz de manter um bom conhecimento da topologia da rede, bem como das suas ligações. Do ponto de vista de escalabilidade, a cooperação do ACOR é seletiva, o que significa que as informações de controlo são trocadas de forma dinâmica apenas entre os CDPs analisados. Além disso, a sincronização é feita através do conceito proposto de Recursos Virtuais Sobre-Provisionado (VOPR), que partilha as reservas de cada interface para cada árvore que usa a interface. Assim, cada CDP pode processar pedidos de sessão numa ou mais árvores, sem a necessidade de sincronização entre os CDPs correlacionados, enquanto o VOPR da árvore não estiver esgotado. Os resultados analíticos e de simulação demonstram que o controlo de sobre-reserva é agregado em cenários descentralizados, mantendo a sinalização de QoS baixa sem perda de largura de banda. Também é desenvolvido um protocolo de controlo de sinalização chamado ACOR Protocol (ACOR-P) para suportar as arquitecturas de centralização e descentralização deste trabalho. O ACOR Estendido (E-ACOR) agrega a VOPR de todas as árvores que se originam no mesmo CDP, e mais pedidos de sessão podem ser processados sem a necessidade de sincronização quando comparado com ACOR. Além disso, E-ACOR introduz um mecanismo para controlar as informações àcerca do congestionamento da rede, e impede a sincronização desnecessária durante o tempo de congestionamento quando os VOPRs esgotam consoante cada pedido de sessão. A avaliação de desempenho, através de resultados analíticos e de simulação, mostra a superioridade do E-ACOR em minimizar o controlo geral da carga da sinalização, mantendo todas as vantagens do ACOR, sem apresentar violações de QoS ou desperdício de recursos. A última parte desta Tese inclui a proposta para recuperação a falhas, o Survivability ACOR (SACOR), o qual permite ter QoS estável em caso de falhas de ligações e nós. Os resultados de desempenho analisados mostram uma capacidade flexível de sobrevivência caracterizada por um tempo de convergência rápido e diferenciação de tráfego com uma utilização eficiente dos recursos. Em resumo, os mecanismos de controlo de recursos propostos nesta Tese fornecem um suporte eficiente e escalável para controlo da rede, como também para os seus principais sub-sistemas (por exemplo, QoS, controlo de recursos, engenharia de tráfego, multicast, etc) e, assim, permitir a otimização do desempenho da rede a nível do controlo global

Online learning on the programmable dataplane

This thesis makes the case for managing computer networks with datadriven methods automated statistical inference and control based on measurement data and runtime observations—and argues for their tight integration with programmable dataplane hardware to make management decisions faster and from more precise data. Optimisation, defence, and measurement of networked infrastructure are each challenging tasks in their own right, which are currently dominated by the use of hand-crafted heuristic methods. These become harder to reason about and deploy as networks scale in rates and number of forwarding elements, but their design requires expert knowledge and care around unexpected protocol interactions. This makes tailored, per-deployment or -workload solutions infeasible to develop. Recent advances in machine learning offer capable function approximation and closed-loop control which suit many of these tasks. New, programmable dataplane hardware enables more agility in the network— runtime reprogrammability, precise traffic measurement, and low latency on-path processing. The synthesis of these two developments allows complex decisions to be made on previously unusable state, and made quicker by offloading inference to the network. To justify this argument, I advance the state of the art in data-driven defence of networks, novel dataplane-friendly online reinforcement learning algorithms, and in-network data reduction to allow classification of switchscale data. Each requires co-design aware of the network, and of the failure modes of systems and carried traffic. To make online learning possible in the dataplane, I use fixed-point arithmetic and modify classical (non-neural) approaches to take advantage of the SmartNIC compute model and make use of rich device local state. I show that data-driven solutions still require great care to correctly design, but with the right domain expertise they can improve on pathological cases in DDoS defence, such as protecting legitimate UDP traffic. In-network aggregation to histograms is shown to enable accurate classification from fine temporal effects, and allows hosts to scale such classification to far larger flow counts and traffic volume. Moving reinforcement learning to the dataplane is shown to offer substantial benefits to stateaction latency and online learning throughput versus host machines; allowing policies to react faster to fine-grained network events. The dataplane environment is key in making reactive online learning feasible—to port further algorithms and learnt functions, I collate and analyse the strengths of current and future hardware designs, as well as individual algorithms

Journal of Telecommunications and Information Technology

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