An Efficient Uplink Multi-Connectivity Scheme for 5G mmWave Control Plane Applications

The millimeter wave (mmWave) frequencies offer the potential of orders of magnitude increases in capacity for next-generation cellular systems. However, links in mmWave networks are susceptible to blockage and may suffer from rapid variations in quality. Connectivity to multiple cells - at mmWave and/or traditional frequencies - is considered essential for robust communication. One of the challenges in supporting multi-connectivity in mmWaves is the requirement for the network to track the direction of each link in addition to its power and timing. To address this challenge, we implement a novel uplink measurement system that, with the joint help of a local coordinator operating in the legacy band, guarantees continuous monitoring of the channel propagation conditions and allows for the design of efficient control plane applications, including handover, beam tracking and initial access. We show that an uplink-based multi-connectivity approach enables less consuming, better performing, faster and more stable cell selection and scheduling decisions with respect to a traditional downlink-based standalone scheme. Moreover, we argue that the presented framework guarantees (i) efficient tracking of the user in the presence of the channel dynamics expected at mmWaves, and (ii) fast reaction to situations in which the primary propagation path is blocked or not available.Comment: Submitted for publication in IEEE Transactions on Wireless Communications (TWC

Evaluation of Wirelessly Transmitted Video Quality Using a Modular Fuzzy Logic System

Video transmission over wireless computer networks is increasingly popular as new applications emerge and wireless networks become more widespread and reliable. An ability to quantify the quality of a video transmitted using a wireless computer network is important for determining network performance and its improvement. The process requires analysing the images making up the video from the point of view of noise and associated distortion as well as traffic parameters represented by packet delay, jitter and loss. In this study a modular fuzzy logic based system was developed to quantify the quality of video transmission over a wireless computer network. Peak signal to noise ratio, structural similarity index and image difference were used to represent the user's quality of experience (QoE) while packet delay, jitter and percentage packet loss ratio were used to represent traffic related quality of service (QoS). An overall measure of the video quality was obtained by combining QoE and QoS values. Systematic sampling was used to reduce the number of images processed and a novel scheme was devised whereby the images were partitioned to more sensitively localize distortions. To further validate the developed system, a subjective test involving 25 participants graded the quality of the received video. The image partitioning significantly improved the video quality evaluation. The subjective test results correlated with the developed fuzzy logic approach. The video quality assessment developed in this study was compared against a method that uses spatial efficient entropic differencing and consistent results were observed. The study indicated that the developed fuzzy logic approaches could accurately determine the quality of a wirelessly transmitted video

Case Study of Diabetes

Funding Information: L.V.L. would like to acknowledge Fundação para a Ciência e a Tecnologia (FCT—MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI). Publisher Copyright: © 2023 by the authors.European cities should address the climate change challenges, improving quality of life and reducing costs. They need potential smart and digital approaches. Public health (PH) has recognized climate change as a major challenge. The development of urban policies should be guided by evidence-based PH practices. The environmental health determinants and the climate crisis now represent a clear PH threat. The core of the Smart City is sustainability, and its basic condition is active PH. The inclusion of public health into the pillars of the Smart City concept to contribute toward mitigating PH crises, such as the COVID-19 pandemic, is a framework for action. Design Science Research Methodology (DSRM) is used to elicit a Smart Public Health City (SPHEC) framework. A set of PH and smart city experts participated in the DSRM process, using diabetes as a case study. The European Green Deal served as a blueprint for this transformational change toward a healthier and more sustainable city. The SPHEC framework was defined by elucidating clearly the several dimensions of the PH functions within a digital city, via the identification of a set of digital PH services that are required to support the SPHEC framework. This allows for an assessment of the actual benefits that are obtained with the digital health services, and provides evidence for guiding decision-making. The role of digital PH services emerges from the analysis of the SPHEC framework, through the development of proper digital health services within the smart city, strengthening capacity and resilience in future climate emergencies, and motivating policy makers to take this challenge more seriously.publishersversionpublishe

Coverage and Connectivity Analysis of Millimeter Wave Vehicular Networks

The next generations of vehicles will require data transmission rates in the order of terabytes per driving hour, to support advanced automotive services. This unprecedented amount of data to be exchanged goes beyond the capabilities of existing communication technologies for vehicular communication and calls for new solutions. A possible answer to this growing demand for ultra-high transmission speeds can be found in the millimeter-wave (mmWave) bands which, however, are subject to high signal attenuation and challenging propagation characteristics. In particular, mmWave links are typically directional, to benefit from the resulting beamforming gain, and require precise alignment of the transmitter and the receiver beams, an operation which may increase the latency of the communication and lead to deafness due to beam misalignment. In this paper, we propose a stochastic model for characterizing the beam coverage and connectivity probability in mmWave automotive networks. The purpose is to exemplify some of the complex and interesting tradeoffs that have to be considered when designing solutions for vehicular scenarios based on mmWave links. The results show that the performance of the automotive nodes in highly mobile mmWave systems strictly depends on the specific environment in which the vehicles are deployed, and must account for several automotive-specific features such as the nodes speed, the beam alignment periodicity, the base stations density and the antenna geometry.Comment: In press of Elsevier Ad Hoc Network

Enhancing SDN WISE with Slicing Over TSCH

[EN] IWSNs (Industrial Wireless Sensor Networks) have become the next step in the evolution of WSN (Wireless Sensor Networks) due to the nature and demands of modern industry. With this type of network, flexible and scalable architectures can be created that simultaneously support traffic sources with different characteristics. Due to the great diversity of application scenarios, there is a need to implement additional capabilities that can guarantee an adequate level of reliability and that can adapt to the dynamic behavior of the applications in use. The use of SDNs (Software Defined Networks) extends the possibilities of control over the network and enables its deployment at an industrial level. The signaling traffic exchanged between nodes and controller is heavy and must occupy the same channel as the data traffic. This difficulty can be overcome with the segmentation of the traffic into flows, and correct scheduling at the MAC (Medium Access Control) level, known as slices. This article proposes the integration in the SDN controller of a traffic manager, a routing process in charge of assigning different routes according to the different flows, as well as the introduction of the Time Slotted Channel Hopping (TSCH) Scheduler. In addition, the TSCH (Time Slotted Channel Hopping) is incorporated in the SDN-WISE framework (Software Defined Networking solution for Wireless Sensor Networks), and this protocol has been modified to send the TSCH schedule. These elements are jointly responsible for scheduling and segmenting the traffic that will be sent to the nodes through a single packet from the controller and its performance has been evaluated through simulation and a testbed. The results obtained show how flexibility, adaptability, and determinism increase thanks to the joint use of the routing process and the TSCH Scheduler, which makes it possible to create a slicing by flows, which have different quality of service requirements. This in turn helps guarantee their QoS characteristics, increase the PDR (Packet Delivery Ratio) for the flow with the highest priority, maintain the DMR (Deadline Miss Ratio), and increase the network lifetime.This work has been supported by the MCyU (Spanish Ministry of Science and Universities) under the project ATLAS (PGC2018-094151-B-I00), which is partially funded by AEI, FEDER and EU and has been possible thanks to the collaboration of the Instituto Tecnologico de Informatica (ITI) of Valencia.Orozco-Santos, F.; Sempere Paya, VM.; Albero Albero, T.; Silvestre-Blanes, J. (2021). Enhancing SDN WISE with Slicing Over TSCH. Sensors. 21(4):1-29. https://doi.org/10.3390/s21041075S12921

Hierarchical distributed fog-to-cloud data management in smart cities

There is a vast amount of data being generated every day in the world with different formats, quality levels, etc. This new data, together with the archived historical data, constitute the seed for future knowledge discovery and value generation in several fields of science and big data environments. Discovering value from data is a complex computing process where data is the key resource, not only during its processing, but also during its entire life cycle. However, there is still a huge concern about how to organize and manage this data in all fields for efficient usage and exploitation during all data life cycles. Although several specific Data LifeCycle (DLC) models have been recently defined for particular scenarios, we argue that there is no global and comprehensive DLC framework to be widely used in different fields. In particular scenario, smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, Smart City resources management rely on cloud based solutions where sensors data are collected to provide a centralized and rich set of open data. The advantages of cloud-based frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for real-time or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. We have defined a new framework for data management in the context of a Smart City through a global fog to cloud resources management architecture. This model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. In this thesis, we propose many novel ideas in the design of a novel F2C Data Management architecture for smart cities as following. First, we draw and describe a comprehensive scenario agnostic Data LifeCycle model successfully addressing all challenges included in the 6Vs not tailored to any specific environment, but easy to be adapted to fit the requirements of any particular field. Then, we introduce the Smart City Comprehensive Data LifeCycle model, a data management architecture generated from a comprehensive scenario agnostic model, tailored for the particular scenario of Smart Cities. We define the management of each data life phase, and explain its implementation on a Smart City with Fog-to-Cloud (F2C) resources management. And then, we illustrate a novel architecture for data management in the context of a Smart City through a global fog to cloud resources management architecture. We show this model has the advantages of both, fog and cloud, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. As a first experiment for the F2C data management architecture, a real Smart City is analyzed, corresponding to the city of Barcelona, with special emphasis on the layers responsible for collecting the data generated by the deployed sensors. The amount of daily sensors data transmitted through the network has been estimated and a rough projection has been made assuming an exhaustive deployment that fully covers all city. And, we provide some solutions to both reduce the data transmission and improve the data management. Then, we used some data filtering techniques (including data aggregation and data compression) to estimate the network traffic in this model during data collection and compare it with a traditional real system. Indeed, we estimate the total data storage sizes through F2C scenario for Barcelona smart citiesAl món es generen diàriament una gran quantitat de dades, amb diferents formats, nivells de qualitat, etc. Aquestes noves dades, juntament amb les dades històriques arxivades, constitueixen la llavor per al descobriment de coneixement i la generació de valor en diversos camps de la ciència i grans entorns de dades (big data). Descobrir el valor de les dades és un procés complex de càlcul on les dades són el recurs clau, no només durant el seu processament, sinó també durant tot el seu cicle de vida. Tanmateix, encara hi ha una gran preocupació per com organitzar i gestionar aquestes dades en tots els camps per a un ús i explotació eficients durant tots els cicles de vida de les dades. Encara que recentment s'han definit diversos models específics de Data LifeCycle (DLC) per a escenaris particulars, argumentem que no hi ha un marc global i complet de DLC que s'utilitzi àmpliament en diferents camps. En particular, les ciutats intel·ligents són les solucions tecnològiques actuals per fer front als reptes i la complexitat de la creixent densitat urbana. Tradicionalment, la gestió de recursos de Smart City es basa en solucions basades en núvol (cloud computing) on es recopilen dades de sensors per proporcionar un conjunt de dades obert i centralitzat. Les avantatges dels entorns basats en núvol són la seva ubiqüitat, així com una capacitat (gairebé) il·limitada de recursos. Tanmateix, l'accés a dades del núvol implica un gran trànsit de xarxa i, en general, les latències elevades no són apropiades per a solucions crítiques o en temps real, així com també per a riscos de seguretat més elevats. Alternativament, el processament de boira (fog computing) sorgeix com una tecnologia prometedora per absorbir aquests inconvenients. Proposa l'ús de dispositius a la vora per proporcionar recuirsos informàtics més propers i, per tant, reduir el trànsit de la xarxa, reduint les latències dràsticament mentre es millora la seguretat. Hem definit un nou marc per a la gestió de dades en el context d'una ciutat intel·ligent a través d'una arquitectura de gestió de recursos des de la boira fins al núvol (Fog-to-Cloud computing, o F2C). Aquest model té els avantatges combinats de les tecnologies de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es poden utilitzar les grans capacitats informàtiques de la tecnologia en núvol. En aquesta tesi, proposem algunes idees noves en el disseny d'una arquitectura F2C de gestió de dades per a ciutats intel·ligents. En primer lloc, dibuixem i descrivim un model de Data LifeCycle global agnòstic que aborda amb èxit tots els reptes inclosos en els 6V i no adaptats a un entorn específic, però fàcil d'adaptar-se als requisits de qualsevol camp en concret. A continuació, presentem el model de Data LifeCycle complet per a una ciutat intel·ligent, una arquitectura de gestió de dades generada a partir d'un model agnòstic d'escenari global, adaptat a l'escenari particular de ciutat intel·ligent. Definim la gestió de cada fase de la vida de les dades i expliquem la seva implementació en una ciutat intel·ligent amb gestió de recursos F2C. I, a continuació, il·lustrem la nova arquitectura per a la gestió de dades en el context d'una Smart City a través d'una arquitectura de gestió de recursos F2C. Mostrem que aquest model té els avantatges d'ambdues, la tecnologia de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es pot utilitzar la gran capacitat de processament de la tecnologia en núvol. Com a primer experiment per a l'arquitectura de gestió de dades F2C, s'analitza una ciutat intel·ligent real, corresponent a la ciutat de Barcelona, amb especial èmfasi en les capes responsables de recollir les dades generades pels sensors desplegats. S'ha estimat la quantitat de dades de sensors diàries que es transmet a través de la xarxa i s'ha realitzat una projecció aproximada assumint un desplegament exhaustiu que cobreix tota la ciutat

Hierarchical distributed fog-to-cloud data management in smart cities

There is a vast amount of data being generated every day in the world with different formats, quality levels, etc. This new data, together with the archived historical data, constitute the seed for future knowledge discovery and value generation in several fields of science and big data environments. Discovering value from data is a complex computing process where data is the key resource, not only during its processing, but also during its entire life cycle. However, there is still a huge concern about how to organize and manage this data in all fields for efficient usage and exploitation during all data life cycles. Although several specific Data LifeCycle (DLC) models have been recently defined for particular scenarios, we argue that there is no global and comprehensive DLC framework to be widely used in different fields. In particular scenario, smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, Smart City resources management rely on cloud based solutions where sensors data are collected to provide a centralized and rich set of open data. The advantages of cloud-based frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for real-time or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. We have defined a new framework for data management in the context of a Smart City through a global fog to cloud resources management architecture. This model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. In this thesis, we propose many novel ideas in the design of a novel F2C Data Management architecture for smart cities as following. First, we draw and describe a comprehensive scenario agnostic Data LifeCycle model successfully addressing all challenges included in the 6Vs not tailored to any specific environment, but easy to be adapted to fit the requirements of any particular field. Then, we introduce the Smart City Comprehensive Data LifeCycle model, a data management architecture generated from a comprehensive scenario agnostic model, tailored for the particular scenario of Smart Cities. We define the management of each data life phase, and explain its implementation on a Smart City with Fog-to-Cloud (F2C) resources management. And then, we illustrate a novel architecture for data management in the context of a Smart City through a global fog to cloud resources management architecture. We show this model has the advantages of both, fog and cloud, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. As a first experiment for the F2C data management architecture, a real Smart City is analyzed, corresponding to the city of Barcelona, with special emphasis on the layers responsible for collecting the data generated by the deployed sensors. The amount of daily sensors data transmitted through the network has been estimated and a rough projection has been made assuming an exhaustive deployment that fully covers all city. And, we provide some solutions to both reduce the data transmission and improve the data management. Then, we used some data filtering techniques (including data aggregation and data compression) to estimate the network traffic in this model during data collection and compare it with a traditional real system. Indeed, we estimate the total data storage sizes through F2C scenario for Barcelona smart citiesAl món es generen diàriament una gran quantitat de dades, amb diferents formats, nivells de qualitat, etc. Aquestes noves dades, juntament amb les dades històriques arxivades, constitueixen la llavor per al descobriment de coneixement i la generació de valor en diversos camps de la ciència i grans entorns de dades (big data). Descobrir el valor de les dades és un procés complex de càlcul on les dades són el recurs clau, no només durant el seu processament, sinó també durant tot el seu cicle de vida. Tanmateix, encara hi ha una gran preocupació per com organitzar i gestionar aquestes dades en tots els camps per a un ús i explotació eficients durant tots els cicles de vida de les dades. Encara que recentment s'han definit diversos models específics de Data LifeCycle (DLC) per a escenaris particulars, argumentem que no hi ha un marc global i complet de DLC que s'utilitzi àmpliament en diferents camps. En particular, les ciutats intel·ligents són les solucions tecnològiques actuals per fer front als reptes i la complexitat de la creixent densitat urbana. Tradicionalment, la gestió de recursos de Smart City es basa en solucions basades en núvol (cloud computing) on es recopilen dades de sensors per proporcionar un conjunt de dades obert i centralitzat. Les avantatges dels entorns basats en núvol són la seva ubiqüitat, així com una capacitat (gairebé) il·limitada de recursos. Tanmateix, l'accés a dades del núvol implica un gran trànsit de xarxa i, en general, les latències elevades no són apropiades per a solucions crítiques o en temps real, així com també per a riscos de seguretat més elevats. Alternativament, el processament de boira (fog computing) sorgeix com una tecnologia prometedora per absorbir aquests inconvenients. Proposa l'ús de dispositius a la vora per proporcionar recuirsos informàtics més propers i, per tant, reduir el trànsit de la xarxa, reduint les latències dràsticament mentre es millora la seguretat. Hem definit un nou marc per a la gestió de dades en el context d'una ciutat intel·ligent a través d'una arquitectura de gestió de recursos des de la boira fins al núvol (Fog-to-Cloud computing, o F2C). Aquest model té els avantatges combinats de les tecnologies de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es poden utilitzar les grans capacitats informàtiques de la tecnologia en núvol. En aquesta tesi, proposem algunes idees noves en el disseny d'una arquitectura F2C de gestió de dades per a ciutats intel·ligents. En primer lloc, dibuixem i descrivim un model de Data LifeCycle global agnòstic que aborda amb èxit tots els reptes inclosos en els 6V i no adaptats a un entorn específic, però fàcil d'adaptar-se als requisits de qualsevol camp en concret. A continuació, presentem el model de Data LifeCycle complet per a una ciutat intel·ligent, una arquitectura de gestió de dades generada a partir d'un model agnòstic d'escenari global, adaptat a l'escenari particular de ciutat intel·ligent. Definim la gestió de cada fase de la vida de les dades i expliquem la seva implementació en una ciutat intel·ligent amb gestió de recursos F2C. I, a continuació, il·lustrem la nova arquitectura per a la gestió de dades en el context d'una Smart City a través d'una arquitectura de gestió de recursos F2C. Mostrem que aquest model té els avantatges d'ambdues, la tecnologia de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es pot utilitzar la gran capacitat de processament de la tecnologia en núvol. Com a primer experiment per a l'arquitectura de gestió de dades F2C, s'analitza una ciutat intel·ligent real, corresponent a la ciutat de Barcelona, amb especial èmfasi en les capes responsables de recollir les dades generades pels sensors desplegats. S'ha estimat la quantitat de dades de sensors diàries que es transmet a través de la xarxa i s'ha realitzat una projecció aproximada assumint un desplegament exhaustiu que cobreix tota la ciutat.Postprint (published version

On Dependable Wireless Communications through Multi-Connectivity

The realization of wireless ultra-reliable low-latency communications (URLLC) is one of the key challenges of the fifth generation (5G) of mobile communications systems and beyond. Ensuring ultra-high reliability together with a latency in the (sub-)millisecond range is expected to enable self-driving cars, wireless factory automation, and the Tactile Internet. In wireless communications, reliability is usually only considered as percentage of successful packet delivery, aiming for 1 − 10⁻⁵ up to 1 − 10⁻⁹ in URLLC