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

Provisioning Ultra-Low Latency Services in Softwarized Network for the Tactile Internet

The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet is envisioned to deliver real-time control and physical tactile experiences remotely in addition to conventional audiovisual data to enable immersive human-to-machine interaction and allow skill-set delivery over networks. To realize the Tactile Internet, two key performance requirements, namely ultra-low latency and ultra-high reliability need to be achieved. However, currently deployed networks are far from meeting these stringent requirements and cannot efficiently cope with dynamic service arrivals/departures and the significant growth of traffic demands. To fulfill these requirements, a softwarized network enabled by network function virtualization (NFV) and software-defined network (SDN) technologies is introduced as a new promising concept of a future network due to its flexibility, agility, scalability and cost efficiency. Despite these benefits, provisioning Tactile Internet network services (NSs) in an NFV-based infrastructure remains a challenge, as network resources must be allocated for virtual network function (VNF) deployment and traffic routing in such a way that the stringent requirements are met, and network operator’s objectives are optimized. This problem is also well-known, as NFV resource allocation (NFV-RA) and can be further divided into three stages: (i) VNF composition, (ii) VNF embedding/placement and (iii) VNF scheduling. This thesis addresses challenges on NFV-RA for Tactile Internet NSs, especially ultra-low latency NSs. We first conduct a survey on architectural and algorithmic solutions proposed so far for the Tactile Internet. Second, we propose a joint VNF composition and embedding algorithm to efficiently determine the number of VNF instances to form a VNF forward graph (VNF-FG) and their embedding locations to serve ultra-low latency NSs, as in some cases, multiple instances of each VNF type with proper embedding may be needed to guarantee the stringent latency requirements. The proposed algorithm relies on a Tabu search method to solve the problem with a reasonable time. Third, we introduce real-time VNF embedding algorithms to efficiently support ultra-low latency NSs that require fast service provisioning. By assuming that a VNF-FG is given, our proposed algorithms aim to minimize the cost while meeting the stringent latency requirement. Finally, we focus on a joint VNF embedding and scheduling problem, assuming that ultra-low latency NSs can arrive in the network any time and have specific service deadlines. Moreover, VNF instances once deployed can be shared by multiple NSs. With these assumptions, we aim to optimally determine whether to schedule NSs on already deployed VNFs or to deploy new VNFs and schedule them on newly deployed VNFs to maximize profits while guaranteeing the stringent service deadlines. Two efficient heuristics are introduced to solve this problem with a feasible time

Automated service provisioning and hierarchical SLA management in 5G systems

Empowered by network softwarization, 5G systems have become the key enabler to foster the digital transformation of the vertical industries by expanding the scope of traditional mobile networks and enriching the network service offerings. To make this a reality, we propose an automation solution for vertical services provisioning and hierarchical Service Level Agreement (SLA) management. Service scaling is one of the most essential operations to adapt the service deployments and resource allocations to ensure SLA fulfilment. Three different scaling levels are addressed in this work: application-, service- and resource-level. We have implemented our solution in a proof-of-concept of a virtualized mobile network platform, spanning over three geographically-distributed sites. To evaluate our solution, we leverage field tests, focusing on automotive vertical services comprising a mission-critical application (collision-avoidance) and an entertainment one (video streaming). The results demonstrate the excellent performance of our solution, and its ability to automatically deploy vertical services and ensure their SLAs through different levels of service scaling.This work has been partially supported by European Commission H2020 5GPPP through the 5G-TRANSFORMER and 5GROWTH projects (Grants No. 761536 and 856709)

Systemic circular economy solutions for fiber reinforced composites

This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials

Virtualisation and resource allocation in MECEnabled metro optical networks

The appearance of new network services and the ever-increasing network traffic and number of connected devices will push the evolution of current communication networks towards the Future Internet. In the area of optical networks, wavelength routed optical networks (WRONs) are evolving to elastic optical networks (EONs) in which, thanks to the use of OFDM or Nyquist WDM, it is possible to create super-channels with custom-size bandwidth. The basic element in these networks is the lightpath, i.e., all-optical circuits between two network nodes. The establishment of lightpaths requires the selection of the route that they will follow and the portion of the spectrum to be used in order to carry the requested traffic from the source to the destination node. That problem is known as the routing and spectrum assignment (RSA) problem, and new algorithms must be proposed to address this design problem. Some early studies on elastic optical networks studied gridless scenarios, in which a slice of spectrum of variable size is assigned to a request. However, the most common approach to the spectrum allocation is to divide the spectrum into slots of fixed width and allocate multiple, consecutive spectrum slots to each lightpath, depending on the requested bandwidth. Moreover, EONs also allow the proposal of more flexible routing and spectrum assignment techniques, like the split-spectrum approach in which the request is divided into multiple "sub-lightpaths". In this thesis, four RSA algorithms are proposed combining two different levels of flexibility with the well-known k-shortest paths and first fit heuristics. After comparing the performance of those methods, a novel spectrum assignment technique, Best Gap, is proposed to overcome the inefficiencies emerged when combining the first fit heuristic with highly flexible networks. A simulation study is presented to demonstrate that, thanks to the use of Best Gap, EONs can exploit the network flexibility and reduce the blocking ratio. On the other hand, operators must face profound architectural changes to increase the adaptability and flexibility of networks and ease their management. Thanks to the use of network function virtualisation (NFV), the necessary network functions that must be applied to offer a service can be deployed as virtual appliances hosted by commodity servers, which can be located in data centres, network nodes or even end-user premises. The appearance of new computation and networking paradigms, like multi-access edge computing (MEC), may facilitate the adaptation of communication networks to the new demands. Furthermore, the use of MEC technology will enable the possibility of installing those virtual network functions (VNFs) not only at data centres (DCs) and central offices (COs), traditional hosts of VFNs, but also at the edge nodes of the network. Since data processing is performed closer to the enduser, the latency associated to each service connection request can be reduced. MEC nodes will be usually connected between them and with the DCs and COs by optical networks. In such a scenario, deploying a network service requires completing two phases: the VNF-placement, i.e., deciding the number and location of VNFs, and the VNF-chaining, i.e., connecting the VNFs that the traffic associated to a service must transverse in order to establish the connection. In the chaining process, not only the existence of VNFs with available processing capacity, but the availability of network resources must be taken into account to avoid the rejection of the connection request. Taking into consideration that the backhaul of this scenario will be usually based on WRONs or EONs, it is necessary to design the virtual topology (i.e., the set of lightpaths established in the networks) in order to transport the tra c from one node to another. The process of designing the virtual topology includes deciding the number of connections or lightpaths, allocating them a route and spectral resources, and finally grooming the traffic into the created lightpaths. Lastly, a failure in the equipment of a node in an NFV environment can cause the disruption of the SCs traversing the node. This can cause the loss of huge amounts of data and affect thousands of end-users. In consequence, it is key to provide the network with faultmanagement techniques able to guarantee the resilience of the established connections when a node fails. For the mentioned reasons, it is necessary to design orchestration algorithms which solve the VNF-placement, chaining and network resource allocation problems in 5G networks with optical backhaul. Moreover, some versions of those algorithms must also implements protection techniques to guarantee the resilience system in case of failure. This thesis makes contribution in that line. Firstly, a genetic algorithm is proposed to solve the VNF-placement and VNF-chaining problems in a 5G network with optical backhaul based on star topology: GASM (genetic algorithm for effective service mapping). Then, we propose a modification of that algorithm in order to be applied to dynamic scenarios in which the reconfiguration of the planning is allowed. Furthermore, we enhanced the modified algorithm to include a learning step, with the objective of improving the performance of the algorithm. In this thesis, we also propose an algorithm to solve not only the VNF-placement and VNF-chaining problems but also the design of the virtual topology, considering that a WRON is deployed as the backhaul network connecting MEC nodes and CO. Moreover, a version including individual VNF protection against node failure has been also proposed and the effect of using shared/dedicated and end-to-end SC/individual VNF protection schemes are also analysed. Finally, a new algorithm that solves the VNF-placement and chaining problems and the virtual topology design implementing a new chaining technique is also proposed. Its corresponding versions implementing individual VNF protection are also presented. Furthermore, since the method works with any type of WDM mesh topologies, a technoeconomic study is presented to compare the effect of using different network topologies in both the network performance and cost.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

Systemic Circular Economy Solutions for Fiber Reinforced Composites

This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials

Intelligent Multi-Dimensional Resource Management in MEC-Assisted Vehicular Networks

Benefiting from advances in the automobile industry and wireless communication technologies, the vehicular network has been emerged as a key enabler of intelligent transportation services. Allowing real-time information exchanging between vehicle and everything, traffic safety and efficiency are significantly enhanced, and ubiquitous Internet access is enabled to support new data services and applications. However, with more and more services and applications, mobile data traffic generated by vehicles has been increasing and the issue on the overloaded computing task has been getting worse. Because of the limitation of spectrum and vehicles' on-board computing and caching resources, it is challenging to promote vehicular networking technologies to support the emerging services and applications, especially those requiring sensitive delay and diverse resources. To overcome these challenges, in this thesis, we propose a new vehicular network architecture and design efficient resource management schemes to support the emerging applications and services with different levels of quality-of-service (QoS) guarantee. Firstly, we propose a multi-access edge computing (MEC)-assisted vehicular network (MVNET) architecture that integrates the concepts of software-defined networking (SDN) and network function virtualization (NFV). With MEC, the interworking of multiple wireless access technologies can be realized to exploit the diversity gain over a wide range of radio spectrum, and at the same time, vehicle's computing/caching tasks can be offloaded to and processed by the MEC servers. By enabling NFV in MEC, different functions can be programmed on the server to support diversified vehicular applications, thus enhancing the server's flexibility. Moreover, by using SDN concepts in MEC, a unified control plane interface and global information can be provided, and by subsequently using this information, intelligent traffic steering and efficient resource management can be achieved. Secondly, under the proposed MVNET architecture, we propose a dynamic spectrum management framework to improve spectrum resource utilization while guaranteeing QoS requirements for different applications, in which, spectrum slicing, spectrum allocating, and transmit power controlling are jointly considered. Accordingly, three non-convex network utility maximization problems are formulated to slice spectrum among base stations (BSs), allocate spectrum among vehicles associated with the same BS, and control transmit powers of BSs, respectively. Via linear programming relaxation and first-order Taylor series approximation, these problems are transformed into tractable forms and then are jointly solved by a proposed alternate concave search algorithm. As a result, optimal spectrum slicing ratios among BSs, optimal BS-vehicle association patterns, optimal fractions of spectrum resources allocated to vehicles, and optimal transmit powers of BSs are obtained. Based on our simulation, a high aggregate network utility is achieved by the proposed spectrum management scheme compared with two existing schemes. Thirdly, we study the joint allocation of the spectrum, computing, and caching resources in MVNETs. To support different vehicular applications, we consider two typical MVNET architectures and formulate multi-dimensional resource optimization problems accordingly, which are usually with high computation complexity and overlong problem-solving time. Thus, we exploit reinforcement learning to transform the two formulated problems and solve them by leveraging the deep deterministic policy gradient (DDPG) and hierarchical learning architectures. Via off-line training, the network dynamics can be automatically learned and appropriate resource allocation decisions can be rapidly obtained to satisfy the QoS requirements of vehicular applications. From simulation results, the proposed resource management schemes can achieve high delay/QoS satisfaction ratios. Fourthly, we extend the proposed MVNET architecture to an unmanned aerial vehicle (UAV)-assisted MVNET and investigate multi-dimensional resource management for it. To efficiently provide on-demand resource access, the macro eNodeB and UAV, both mounted with MEC servers, cooperatively make association decisions and allocate proper amounts of resources to vehicles. Since there is no central controller, we formulate the resource allocation at the MEC servers as a distributive optimization problem to maximize the number of offloaded tasks while satisfying their heterogeneous QoS requirements, and then solve it with a multi-agent DDPG (MADDPG)-based method. Through centrally training the MADDPG model offline, the MEC servers, acting as learning agents, then can rapidly make vehicle association and resource allocation decisions during the online execution stage. From our simulation results, the MADDPG-based method can achieve a comparable convergence rate and higher delay/QoS satisfaction ratios than the benchmarks. In summary, we have proposed an MEC-assisted vehicular network architecture and investigated the spectrum slicing and allocation, and multi-dimensional resource allocation in the MEC- and/or UAV-assisted vehicular networks in this thesis. The proposed architecture and schemes should provide useful guidelines for future research in multi-dimensional resource management scheme designing and resource utilization enhancement in highly dynamic wireless networks with diversified data services and applications

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Systemic Circular Economy Solutions for Fiber Reinforced Composites

This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials