Networks, Communication, and Computing Vol. 2

Networks, communications, and computing have become ubiquitous and inseparable parts of everyday life. This book is based on a Special Issue of the Algorithms journal, and it is devoted to the exploration of the many-faceted relationship of networks, communications, and computing. The included papers explore the current state-of-the-art research in these areas, with a particular interest in the interactions among the fields

Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

A Comprehensive Review of D2D Communication in 5G and B5G Networks

The evolution of Device-to-device (D2D) communication represents a significant breakthrough within the realm of mobile technology, particularly in the context of 5G and beyond 5G (B5G) networks. This innovation streamlines the process of data transfer between devices that are in close physical proximity to each other. D2D communication capitalizes on the capabilities of nearby devices to communicate directly with one another, thereby optimizing the efficient utilization of available network resources, reducing latency, enhancing data transmission speed, and increasing the overall network capacity. In essence, it empowers more effective and rapid data sharing among neighboring devices, which is especially advantageous within the advanced landscape of mobile networks such as 5G and B5G. The development of D2D communication is largely driven by mobile operators who gather and leverage short-range communications data to propel this technology forward. This data is vital for maintaining proximity-based services and enhancing network performance. The primary objective of this research is to provide a comprehensive overview of recent progress in different aspects of D2D communication, including the discovery process, mode selection methods, interference management, power allocation, and how D2D is employed in 5G technologies. Furthermore, the study also underscores the unresolved issues and identifies the challenges associated with D2D communication, shedding light on areas that need further exploration and developmen

SDN-based VANET routing: A comprehensive survey on architectures, protocols, analysis, and future challenges

As the automotive and telecommunication industries advance, more vehicles are becoming connected, leading to the realization of intelligent transportation systems (ITS). Vehicular ad-hoc network (VANET) supports various ITS services, including safety, convenience, and infotainment services for drivers and passengers. Generally, such services are realized through data sharing among vehicles and nearby infrastructures or vehicles over multi-hop data routing mechanisms. Vehicular data routing faces many challenges caused by vehicle dynamicity, intermittent connectivity, and diverse application requirements. Consequently, the software-defined networking (SDN) paradigm offers unique features such as programmability and flexibility to enhance vehicular network performance and management and meet the quality of services (QoS) requirements of various VANET services. Recently, VANET routing protocols have been improved using the multilevel knowledge and an up-to-date global view of traffic conditions offered by SDN technology. The primary objective of this study is to furnish comprehensive information regarding the current SDN-based VANET routing protocols, encompassing intricate details of their underlying mechanisms, forwarding algorithms, and architectural considerations. Each protocol will be thoroughly examined individually, elucidating its strengths, weaknesses, and proposed enhancements. Also, the software-defined vehicular network (SDVN) architectures are presented according to their operation modes and controlling degree. Then, the potential of SDN-based VANET is explored from the aspect of routing and the design requirements of routing protocols in SDVNs. SDVN routing algorithms are uniquely classified according to various criteria. In addition, a complete comparative analysis will be achieved to analyze the protocols regarding performance, optimization, and simulation results. Finally, the challenges and upcoming research directions for developing such protocols are widely stated here. By presenting such insights, this paper provides a comprehensive overview and inspires researchers to enhance existing protocols and explore novel solutions, thereby paving the way for innovation in this field

NFV orchestration in edge and fog scenarios

Mención Internacional en el título de doctorLas infraestructuras de red actuales soportan una variedad diversa de servicios como video bajo demanda, video conferencias, redes sociales, sistemas de educación, o servicios de almacenamiento de fotografías. Gran parte de la población mundial ha comenzado a utilizar estos servicios, y los utilizan diariamente. Proveedores de Cloud y operadores de infraestructuras de red albergan el tráfico de red generado por estos servicios, y sus tareas de gestión no solo implican realizar el enrutamiento del tráfico, sino también el procesado del tráfico de servicios de red. Tradicionalmente, el procesado del tráfico ha sido realizado mediante aplicaciones/ programas desplegados en servidores que estaban dedicados en exclusiva a tareas concretas como la inspección de paquetes. Sin embargo, en los últimos anos los servicios de red se han virtualizado y esto ha dado lugar al paradigma de virtualización de funciones de red (Network Function Virtualization (NFV) siguiendo las siglas en ingles), en el que las funciones de red de un servicio se ejecutan en contenedores o máquinas virtuales desacopladas de la infraestructura hardware. Como resultado, el procesado de tráfico se ha ido haciendo más flexible gracias al laxo acople del software y hardware, y a la posibilidad de compartir funciones de red típicas, como firewalls, entre los distintos servicios de red. NFV facilita la automatización de operaciones de red, ya que tareas como el escalado, o la migración son típicamente llevadas a cabo mediante un conjunto de comandos previamente definidos por la tecnología de virtualización pertinente, bien mediante contenedores o máquinas virtuales. De todos modos, sigue siendo necesario decidir el en rutamiento y procesado del tráfico de cada servicio de red. En otras palabras, que servidores tienen que encargarse del procesado del tráfico, y que enlaces de la red tienen que utilizarse para que las peticiones de los usuarios lleguen a los servidores finales, es decir, el conocido como embedding problem. Bajo el paraguas del paradigma NFV, a este problema se le conoce en inglés como Virtual Network Embedding (VNE), y esta tesis utiliza el termino “NFV orchestration algorithm” para referirse a los algoritmos que resuelven este problema. El problema del VNE es NP-hard, lo cual significa que que es imposible encontrar una solución optima en un tiempo polinómico, independientemente del tamaño de la red. Como consecuencia, la comunidad investigadora y de telecomunicaciones utilizan heurísticos que encuentran soluciones de manera más rápida que productos para la resolución de problemas de optimización. Tradicionalmente, los “NFV orchestration algorithms” han intentado minimizar los costes de despliegue derivados de las soluciones asociadas. Por ejemplo, estos algoritmos intentan no consumir el ancho de banda de la red, y usar rutas cortas para no utilizar tantos recursos. Además, una tendencia reciente ha llevado a la comunidad investigadora a utilizar algoritmos que minimizan el consumo energético de los servicios desplegados, bien mediante la elección de dispositivos con un consumo energético más eficiente, o mediante el apagado de dispositivos de red en desuso. Típicamente, las restricciones de los problemas de VNE se han resumido en un conjunto de restricciones asociadas al uso de recursos y consumo energético, y las soluciones se diferenciaban por la función objetivo utilizada. Pero eso era antes de la 5a generación de redes móviles (5G) se considerase en el problema de VNE. Con la aparición del 5G, nuevos servicios de red y casos de uso entraron en escena. Los estándares hablaban de comunicaciones ultra rápidas y fiables (Ultra-Reliable and Low Latency Communications (URLLC) usando las siglas en inglés) con latencias por debajo de unos pocos milisegundos y fiabilidades del 99.999%, una banda ancha mejorada (enhanced Mobile Broadband (eMBB) usando las siglas en inglés) con notorios incrementos en el flujo de datos, e incluso la consideración de comunicaciones masivas entre maquinas (Massive Machine-Type Communications (mMTC) usando las siglas en inglés) entre dispositivos IoT. Es más, paradigmas como edge y fog computing se incorporaron a la tecnología 5G, e introducían la idea de tener dispositivos de computo más cercanos al usuario final. Como resultado, el problema del VNE tenía que incorporar los nuevos requisitos como restricciones a tener en cuenta, y toda solución debía satisfacer bajas latencias, alta fiabilidad, y mayores tasas de transmisión. Esta tesis estudia el problema des VNE, y propone algunos heurísticos que lidian con las restricciones asociadas a servicios 5G en escenarios edge y fog, es decir, las soluciones propuestas se encargan de asignar funciones virtuales de red a servidores, y deciden el enrutamiento del trafico en las infraestructuras 5G con dispositivos edge y fog. Para evaluar el rendimiento de las soluciones propuestas, esta tesis estudia en primer lugar la generación de grafos que representan redes 5G. Los mecanismos propuestos para la generación de grafos sirven para representar distintos escenarios 5G. En particular, escenarios de federación en los que varios dominios comparten recursos entre ellos. Los grafos generados también representan servidores en el edge, así como dispositivos fog con una batería limitada. Además, estos grafos tienen en cuenta los requisitos de estándares, y la demanda que se espera en las redes 5G. La generación de grafos propuesta sirve para representar escenarios federación en los que varios dominios comparten recursos entre ellos, y redes 5G con servidores edge, así como dispositivos fog estáticos o móviles con una batería limitada. Los grafos generados para infraestructuras 5G tienen en cuenta los requisitos de estándares, y la demanda de red que se espera en las redes 5G. Además, los grafos son diferentes en función de la densidad de población, y el área de estudio, es decir, si es una zona industrial, una autopista, o una zona urbana. Tras detallar la generación de grafos que representan redes 5G, esta tesis propone algoritmos de orquestación NFV para resolver con el problema del VNE. Primero, se centra en escenarios federados en los que los servicios de red se tienen que asignar no solo a la infraestructura de un dominio, sino a los recursos compartidos en la federación de dominios. Dos problemas diferentes han sido estudiados, uno es el problema del VNE propiamente dicho sobre una infraestructura federada, y el otro es la delegación de servicios de red. Es decir, si un servicio de red se debe desplegar localmente en un dominio, o en los recursos compartidos por la federación de dominios; a sabiendas de que el último caso supone el pago de cuotas por parte del dominio local a cambio del despliegue del servicio de red. En segundo lugar, esta tesis propone OKpi, un algoritmo de orquestación NFV para conseguir la calidad de servicio de las distintas slices de las redes 5G. Conceptualmente, el slicing consiste en partir la red de modo que cada servicio de red sea tratado de modo diferente dependiendo del trozo al que pertenezca. Por ejemplo, una slice de eHealth reservara los recursos de red necesarios para conseguir bajas latencias en servicios como operaciones quirúrgicas realizadas de manera remota. Cada trozo (slice) está destinado a unos servicios específicos con unos requisitos muy concretos, como alta fiabilidad, restricciones de localización, o latencias de un milisegundo. OKpi es un algoritmo de orquestación NFV que consigue satisfacer los requisitos de servicios de red en los distintos trozos, o slices de la red. Tras presentar OKpi, la tesis resuelve el problema del VNE en redes 5G con dispositivos fog estáticos y móviles. El algoritmo de orquestación NFV presentado tiene en cuenta las limitaciones de recursos de computo de los dispositivos fog, además de los problemas de falta de cobertura derivados de la movilidad de los dispositivos. Para concluir, esta tesis estudia el escalado de servicios vehiculares Vehicle-to-Network (V2N), que requieren de bajas latencias para servicios como la prevención de choques, avisos de posibles riesgos, y conducción remota. Para estos servicios, los atascos y congestiones en la carretera pueden causar el incumplimiento de los requisitos de latencia. Por tanto, es necesario anticiparse a esas circunstancias usando técnicas de series temporales que permiten saber el tráfico inminente en los siguientes minutos u horas, para así poder escalar el servicio V2N adecuadamente.Current network infrastructures handle a diverse range of network services such as video on demand services, video-conferences, social networks, educational systems, or photo storage services. These services have been embraced by a significant amount of the world population, and are used on a daily basis. Cloud providers and Network operators’ infrastructures accommodate the traffic rates that the aforementioned services generate, and their management tasks do not only involve the traffic steering, but also the processing of the network services’ traffic. Traditionally, the traffic processing has been assessed via applications/programs deployed on servers that were exclusively dedicated to a specific task as packet inspection. However, in recent years network services have stated to be virtualized and this has led to the Network Function Virtualization (Network Function Virtualization (NFV)) paradigm, in which the network functions of a service run on containers or virtual machines that are decoupled from the hardware infrastructure. As a result, the traffic processing has become more flexible because of the loose coupling between software and hardware, and the possibility of sharing common network functions, as firewalls, across multiple network services. NFV eases the automation of network operations, since scaling and migrations tasks are typically performed by a set of commands predefined by the virtualization technology, either containers or virtual machines. However, it is still necessary to decide the traffic steering and processing of every network service. In other words, which servers will hold the traffic processing, and which are the network links to be traversed so the users’ requests reach the final servers, i.e., the network embedding problem. Under the umbrella of NFV, this problem is known as Virtual Network Embedding (VNE), and this thesis refers as “NFV orchestration algorithms” to those algorithms solving such a problem. The VNE problem is a NP-hard, meaning that it is impossible to find optimal solutions in polynomial time, no matter the network size. As a consequence, the research and telecommunications community rely on heuristics that find solutions quicker than a commodity optimization solver. Traditionally, NFV orchestration algorithms have tried to minimize the deployment costs derived from their solutions. For example, they try to not exhaust the network bandwidth, and use short paths to use less network resources. Additionally, a recent tendency led the research community towards algorithms that minimize the energy consumption of the deployed services, either by selecting more energy efficient devices or by turning off those network devices that remained unused. VNE problem constraints were typically summarized in a set of resources/energy constraints, and the solutions differed on which objectives functions were aimed for. But that was before 5th generation of mobile networks (5G) were considered in the VNE problem. With the appearance of 5G, new network services and use cases started to emerge. The standards talked about Ultra Reliable Low Latency Communication (Ultra-Reliable and Low Latency Communications (URLLC)) with latencies below few milliseconds and 99.999% reliability, an enhanced mobile broadband (enhanced Mobile Broadband (eMBB)) with significant data rate increases, and even the consideration of massive machine-type communications (Massive Machine-Type Communications (mMTC)) among Internet of Things (IoT) devices. Moreover, paradigms such as edge and fog computing blended with the 5G technology to introduce the idea of having computing devices closer to the end users. As a result, the VNE problem had to incorporate the new requirements as constraints to be taken into account, and every solution should either satisfy low latencies, high reliability, or larger data rates. This thesis studies the VNE problem, and proposes some heuristics tackling the constraints related to 5G services in Edge and fog scenarios, that is, the proposed solutions assess the assignment of Virtual Network Functions to resources, and the traffic steering across 5G infrastructures that have Edge and Fog devices. To evaluate the performance of the proposed solutions, the thesis studies first the generation of graphs that represent 5G networks. The proposed mechanisms to generate graphs serve to represent diverse 5G scenarios. In particular federation scenarios in which several domains share resources among themselves. The generated graphs also represent edge servers, so as fog devices with limited battery capacity. Additionally, these graphs take into account the standard requirements, and the expected demand for 5G networks. Moreover, the graphs differ depending on the density of population, and the area of study, i.e., whether it is an industrial area, a highway, or an urban area. After detailing the generation of graphs representing the 5G networks, this thesis proposes several NFV orchestration algorithms to tackle the VNE problem. First, it focuses on federation scenarios in which network services should be assigned not only to a single domain infrastructure, but also to the shared resources of the federation of domains. Two different problems are studied, one being the VNE itself over a federated infrastructure, and the other the delegation of network services. That is, whether a network service should be deployed in a local domain, or in the pool of resources of the federation domain; knowing that the latter charges the local domain for hosting the network service. Second, the thesis proposes OKpi, a NFV orchestration algorithm to meet 5G network slices quality of service. Conceptually, network slicing consists in splitting the network so network services are treated differently based on the slice they belong to. For example, an eHealth network slice will allocate the network resources necessary to meet low latencies for network services such as remote surgery. Each network slice is devoted to specific services with very concrete requirements, as high reliability, location constraints, or 1ms latencies. OKpi is a NFV orchestration algorithm that meets the network service requirements among different slices. It is based on a multi-constrained shortest path heuristic, and its solutions satisfy latency, reliability, and location constraints. After presenting OKpi, the thesis tackles the VNE problem in 5G networks with static/moving fog devices. The presented NFV orchestration algorithm takes into account the limited computing resources of fog devices, as well as the out-of-coverage problems derived from the devices’ mobility. To conclude, this thesis studies the scaling of Vehicle-to-Network (V2N) services, which require low latencies for network services as collision avoidance, hazard warning, and remote driving. For these services, the presence of traffic jams, or high vehicular traffic congestion lead to the violation of latency requirements. Hence, it is necessary to anticipate to such circumstances by using time-series techniques that allow to derive the incoming vehicular traffic flow in the next minutes or hours, so as to scale the V2N service accordingly.The 5G Exchange (5GEx) project (2015-2018) was an EU-funded project (H2020-ICT-2014-2 grant agreement 671636). The 5G-TRANSFORMER project (2017-2019) is an EU-funded project (H2020-ICT-2016-2 grant agreement 761536). The 5G-CORAL project (2017-2019) is an EU-Taiwan project (H2020-ICT-2016-2 grant agreement 761586).Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Ioannis Stavrakakis.- Secretario: Pablo Serrano Yáñez-Mingot.- Vocal: Paul Horatiu Patra

D4.2 Intelligent D-Band wireless systems and networks initial designs

This deliverable gives the results of the ARIADNE project's Task 4.2: Machine Learning based network intelligence. It presents the work conducted on various aspects of network management to deliver system level, qualitative solutions that leverage diverse machine learning techniques. The different chapters present system level, simulation and algorithmic models based on multi-agent reinforcement learning, deep reinforcement learning, learning automata for complex event forecasting, system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions. In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project

Network Optimisation for Robotic Aerial Base Stations

One attractive application of unmanned aerial vehicles (UAVs) is to provide wireless coverage when acting as aerial base stations (ABSs). Compared to terrestrial small cells, ABSs have the benefit of flexible deployment, controllable mobility, and dominant line-of-sight channels, so they are expected to play a significant role in next-generation cellular networks. However, introducing this novel non-terrestrial communication device would also bring new challenges, such as requiring different evaluation criteria and being restricted by unexpected resource constraints. With this in mind, this thesis mainly focuses on the network optimisation problems of ABS-assisted networks.Specifically, we first investigate two contradictory metrics, i.e., the information freshness and energy consumption, when an ABS is employed to collect data from ground terminals. A novel multi-return-allowed serving mode is proposed to explore the Pareto optimal trade-off between these two metrics. Secondly, to overcome the functional endurance issue of conventional ABSs, we propose a novel prototype named robotic aerial base stations (RABSs) with grasping capabilities, which can attach autonomously in lampposts or land on other tall urban landforms to serve as small cells with prolonged endurance. By employing this novel ABS prototype, we first study the optimal deployment and operation strategy for RABSs when the mobile traffic demand shows heterogeneity in both spatial and temporal domains. Afterwards, to further explore the use of RABSs in the upcoming 6G era, we investigate two novel application scenarios, that is, an RABS-assisted integrated sensing and communication (ISAC) system and an RABS-aided millimetre-wave (mmWave) backhaul network.The proposed scenarios are formulated as various non-convex problems. By analyzing their constructions, we propose a variety of algorithms to solve them in a reasonable time. A wide set of simulation results shows that the proposed novel prototypes and serving schemes have immense potential in future cellular networks.<br/