AI and IoT Meet Mobile Machines: Towards a Smart Working Site

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)

AI and IoT Meet Mobile Machines

Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT)

Data Processing and Fusion For Multi-Source Wireless Systems

The constant evolution of the telecommunication technologies is one fundamental aspect that characterizes the modern era. In the context of healthcare and security, different scenarios are characterized by the presence of multiple sources of information that can support a large number of innovative services. For example, in emergency scenarios, reliable transmission of heterogeneous information (health conditions, ambient and diagnostic videos) can be a valid support for managing the first-aid operations. The presence of multiple sources of information requires a careful communication management, especially in case of limited transmission resource availability. The objective of my Ph.D. activity is to develop new optimization techniques for multimedia communications, considering emergency scenarios characterized by wireless connectivity. Different criteria are defined in order to prioritize the available heterogeneous information before transmission. The proposed solutions are based on the modern concept of content/context awareness: the transmission parameters are optimized taking into account the informative content of the data and the general context in which the information sources are located. To this purpose, novel cross-layer adaptation strategies are proposed for multiple SVC videos delivered over wireless channel. The objective is to optimize the resource allocation dynamically adjusting the overall transmitted throughput to meet the actual available bandwidth. After introducing a realistic camera network, some numerical results obtained with the proposed techniques are showed. In addition, through numerical simulations the benefits are showed, in terms of QoE, introduced by the proposed adaptive aggregation and transmission strategies applied in the context of emergency scenarios. The proposed solution is fully integrated in European research activities, including the FP7 ICT project CONCERTO. To implement, validate and demonstrate the functionalities of the proposed solutions, extensive transmission simulation campaigns are performed. Hence, the presented solutions are integrated on a common system simulator which is been developed within the CONCERTO project

5G Multi-access Edge Computing: Security, Dependability, and Performance

The main innovation of the Fifth Generation (5G) of mobile networks is the ability to provide novel services with new and stricter requirements. One of the technologies that enable the new 5G services is the Multi-access Edge Computing (MEC). MEC is a system composed of multiple devices with computing and storage capabilities that are deployed at the edge of the network, i.e., close to the end users. MEC reduces latency and enables contextual information and real-time awareness of the local environment. MEC also allows cloud offloading and the reduction of traffic congestion. Performance is not the only requirement that the new 5G services have. New mission-critical applications also require high security and dependability. These three aspects (security, dependability, and performance) are rarely addressed together. This survey fills this gap and presents 5G MEC by addressing all these three aspects. First, we overview the background knowledge on MEC by referring to the current standardization efforts. Second, we individually present each aspect by introducing the related taxonomy (important for the not expert on the aspect), the state of the art, and the challenges on 5G MEC. Finally, we discuss the challenges of jointly addressing the three aspects.Comment: 33 pages, 11 figures, 15 tables. This paper is under review at IEEE Communications Surveys & Tutorials. Copyright IEEE 202

Machine learning enabled millimeter wave cellular system and beyond

Millimeter-wave (mmWave) communication with advantages of abundant bandwidth and immunity to interference has been deemed a promising technology for the next generation network and beyond. With the help of mmWave, the requirements envisioned of the future mobile network could be met, such as addressing the massive growth required in coverage, capacity as well as traffic, providing a better quality of service and experience to users, supporting ultra-high data rates and reliability, and ensuring ultra-low latency. However, due to the characteristics of mmWave, such as short transmission distance, high sensitivity to the blockage, and large propagation path loss, there are some challenges for mmWave cellular network design. In this context, to enjoy the benefits from the mmWave networks, the architecture of next generation cellular network will be more complex. With a more complex network, it comes more complex problems. The plethora of possibilities makes planning and managing a complex network system more difficult. Specifically, to provide better Quality of Service and Quality of Experience for users in the such network, how to provide efficient and effective handover for mobile users is important. The probability of handover trigger will significantly increase in the next generation network, due to the dense small cell deployment. Since the resources in the base station (BS) is limited, the handover management will be a great challenge. Further, to generate the maximum transmission rate for the users, Line-of-sight (LOS) channel would be the main transmission channel. However, due to the characteristics of mmWave and the complexity of the environment, LOS channel is not feasible always. Non-line-of-sight channel should be explored and used as the backup link to serve the users. With all the problems trending to be complex and nonlinear, and the data traffic dramatically increasing, the conventional method is not effective and efficiency any more. In this case, how to solve the problems in the most efficient manner becomes important. Therefore, some new concepts, as well as novel technologies, require to be explored. Among them, one promising solution is the utilization of machine learning (ML) in the mmWave cellular network. On the one hand, with the aid of ML approaches, the network could learn from the mobile data and it allows the system to use adaptable strategies while avoiding unnecessary human intervention. On the other hand, when ML is integrated in the network, the complexity and workload could be reduced, meanwhile, the huge number of devices and data could be efficiently managed. Therefore, in this thesis, different ML techniques that assist in optimizing different areas in the mmWave cellular network are explored, in terms of non-line-of-sight (NLOS) beam tracking, handover management, and beam management. To be specific, first of all, a procedure to predict the angle of arrival (AOA) and angle of departure (AOD) both in azimuth and elevation in non-line-of-sight mmWave communications based on a deep neural network is proposed. Moreover, along with the AOA and AOD prediction, a trajectory prediction is employed based on the dynamic window approach (DWA). The simulation scenario is built with ray tracing technology and generate data. Based on the generated data, there are two deep neural networks (DNNs) to predict AOA/AOD in the azimuth (AAOA/AAOD) and AOA/AOD in the elevation (EAOA/EAOD). Furthermore, under an assumption that the UE mobility and the precise location is unknown, UE trajectory is predicted and input into the trained DNNs as a parameter to predict the AAOA/AAOD and EAOA/EAOD to show the performance under a realistic assumption. The robustness of both procedures is evaluated in the presence of errors and conclude that DNN is a promising tool to predict AOA and AOD in a NLOS scenario. Second, a novel handover scheme is designed aiming to optimize the overall system throughput and the total system delay while guaranteeing the quality of service (QoS) of each user equipment (UE). Specifically, the proposed handover scheme called O-MAPPO integrates the reinforcement learning (RL) algorithm and optimization theory. An RL algorithm known as multi-agent proximal policy optimization (MAPPO) plays a role in determining handover trigger conditions. Further, an optimization problem is proposed in conjunction with MAPPO to select the target base station and determine beam selection. It aims to evaluate and optimize the system performance of total throughput and delay while guaranteeing the QoS of each UE after the handover decision is made. Third, a multi-agent RL-based beam management scheme is proposed, where multiagent deep deterministic policy gradient (MADDPG) is applied on each small-cell base station (SCBS) to maximize the system throughput while guaranteeing the quality of service. With MADDPG, smart beam management methods can serve the UEs more efficiently and accurately. Specifically, the mobility of UEs causes the dynamic changes of the network environment, the MADDPG algorithm learns the experience of these changes. Based on that, the beam management in the SCBS is optimized according the reward or penalty when severing different UEs. The approach could improve the overall system throughput and delay performance compared with traditional beam management methods. The works presented in this thesis demonstrate the potentiality of ML when addressing the problem from the mmWave cellular network. Moreover, it provides specific solutions for optimizing NLOS beam tracking, handover management and beam management. For NLOS beam tracking part, simulation results show that the prediction errors of the AOA and AOD can be maintained within an acceptable range of ±2. Further, when it comes to the handover optimization part, the numerical results show the system throughput and delay are improved by 10% and 25%, respectively, when compared with two typical RL algorithms, Deep Deterministic Policy Gradient (DDPG) and Deep Q-learning (DQL). Lastly, when it considers the intelligent beam management part, numerical results reveal the convergence performance of the MADDPG and the superiority in improving the system throughput compared with other typical RL algorithms and the traditional beam management method

Spectral, Energy and Computation Efficiency in Future 5G Wireless Networks

Wireless technology has revolutionized the way people communicate. From first generation, or 1G, in the 1980s to current, largely deployed 4G in the 2010s, we have witnessed not only a technological leap, but also the reformation of associated applications. It is expected that 5G will become commercially available in 2020. 5G is driven by ever-increasing demands for high mobile traffic, low transmission delay, and massive numbers of connected devices. Today, with the popularity of smart phones, intelligent appliances, autonomous cars, and tablets, communication demands are higher than ever, especially when it comes to low-cost and easy-access solutions. Existing communication architecture cannot fulfill 5G’s needs. For example, 5G requires connection speeds up to 1,000 times faster than current technology can provide. Also, from transmitter side to receiver side, 5G delays should be less than 1ms, while 4G targets a 5ms delay speed. To meet these requirements, 5G will apply several disruptive techniques. We focus on two of them: new radio and new scheme. As for the former, we study the non-orthogonal multiple access (NOMA) and as for the latter, we use mobile edge computing (MEC). Traditional communication systems allow users to communicate alternatively, which clearly avoids inter-user interference, but also caps the connection speed. NOMA, on the other hand, allows multiple users to transmit simultaneously. While NOMA will inevitably cause excessive interference, we prove such interference can be mitigated by an advanced receiver side technique. NOMA has existed on the research frontier since 2013. Since that time, both academics and industry professionals have extensively studied its performance. In this dissertation, our contribution is to incorporate NOMA with several potential schemes, such as relay, IoT, and cognitive radio networks. Furthermore, we reviewed various limitations on NOMA and proposed a more practical model. In the second part, MEC is considered. MEC is a transformation from the previous cloud computing system. In particular, MEC leverages powerful devices nearby and instead of sending information to distant cloud servers, the transmission occurs in closer range, which can effectively reduce communication delay. In this work, we have proposed a new evaluation metric for MEC which can more effectively leverage the trade-off between the amount of computation and the energy consumed thereby. A practical communication system for wearable devices is proposed in the last part, which combines all the techniques discussed above. The challenges for wearable communication are inherent in its diverse needs, as some devices may require low speed but high reliability (factory sensors), while others may need low delay (medical devices). We have addressed these challenges and validated our findings through simulations

Utilização do protocolo IEC 61850 sobre redes de telecomunicações IP

We live in an era where the consumption of energy rises to an almost immeasurable level, jeopardizing the balance of systems when a power failure in the electrical grid occurs. This brought the necessity of making it safer and intelligent, hence emerging the concept of Smart Grid. The IEC 61850 standard was initially designed to operate within substations, yet other potential developments glimpsed to operate not only within substations but also to the outside of them. Based on several communications protocols, including MMS, GOOSE and SV, the IEC 61850 provides the possibility of real-time data exchange, leading to cost savings, increased security and interoperability between different vendors’ devices. Addressing this issue, together with EFACEC and the Institute of Telecommunications of Aveiro, a key question emerged: What are the requirements for the communication between devices in different substations? This MSc dissertation aims to answer this question, as well as to analyse other possible technologies that are suitable at the time of its implementation. With this analysis, a specific technology stands out, the 4G-LTE. A study was conducted recurring to temporal diagrams of the messages, performing with both approaches as described in the standard. Either using the IP or VPN approach, different technologies such as ADSL, Optical Fibre, and the previously referred 4G-LTE were tested. Thereafter, the results of the study are analysed, obtaining this way the conclusions for each one of the approaches, as well for each of the different technologies studied. Last but not least, it is analysed which of the approaches will be more beneficial in the long-term, as well as the necessary future work that must be developed in the different areas of the presented standard.Vivemos numa era em que o consumo de energia cresce a um nível quase imensurável, colocando em causa o equilíbrio de um sistema aquando a ocorrência de uma falha na rede elétrica. Isto trouxe a necessidade de a tornar numa rede mais segura e inteligente, surgindo então o conceito de Smart Grid. O standard IEC 61850 foi inicialmente concebido para operar dentro das subestações, contudo vislumbraram-se outras potencialidades para o aplicar não só dentro, mas também para fora das mesmas. Assente em vários protocolos de comunicação, entre os quais MMS, GOOSE e SV, o IEC 61850 oferece a possibilidade de troca de dados em tempo real, levando a uma redução de custos, um aumento da segurança bem como a interoperabilidade entre os equipamentos dos diferentes vendedores. Abordando este tema em conjunto com a EFACEC e o Instituto de Telecomunicações de Aveiro, houve uma questão se levantou: Quais são as condições requeridas para a comunicação entre os equipamentos das diferentes subestações? Esta dissertação de mestrado visa dar resposta a esta questão, assim como analisar outras possíveis tecnologias a utilizar no momento da sua implementação. Realizada essa análise, houve uma tecnologia que se evidenciou, o 4G-LTE. Foi elaborado um estudo com recurso a diagramas temporais de mensagens, utilizando as duas abordagens descritas no standard. Quer utilizando a abordagem por IP quer utilizando a abordagem por VPN, foram testados em ambos os cenários diferentes tecnologias como a ADSL, Fibra Ótica, bem como o já referido, 4G-LTE. De seguida, são analisados os resultados do estudo, obtendo as devidas conclusões para cada uma das abordagens bem como para cada uma das diferentes tecnologias. Por fim, é analisada qual das abordagens será mais proveitosa a longo prazo, assim como qual o trabalho futuro que deverá ser desenvolvido no que diz respeito às diferentes áreas do standard apresentado.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Visible light and device-to-device communications: system analysis and implementation

Mención internacional en el título de doctorRadio-frequency based wireless communications have revolutionized our society. Thanks to the important wireless communication technologiesWi-Fi, LTE, and so on, people can now enjoy high data rate and perversive connection while surfing the Internet. However, new problems and demands are rising in today’s wireless networks. Increasing capacity demands are requiring more bandwidth and various wireless radio technologies are exacerbating the spectrum problem. Now technologies and paradigms are needed to meet these needs. In this thesis, I investigate two technologies towards this direction: Visible Light Communication (VLC) and Device-to-Device (D2D) communication. Although more and more researchers are becoming interested in VLC, the lacking of an opensource platform for VLC research is perverting the fast investigations of VLC. To solve this problem, I design, implement, and evaluate the first open-source platform OpenVLC for embedded VLC research. OpenVLC employs cost-efficient and off-the-shelf optical components and electronics to provide a research platform. The software solutions are developed as a Linux driver and can easily connect to the TCP/IP layers. This allows for the adoption of various Linux diagnostic tools to evaluate the VLC’s properties and performance. Based on OpenVLC, I propose a new MAC protocol that enable the intra-frame bidirectional transmissions in networks of visible LEDs. The method adopts only a single LED at each node for both transmission and reception. Through this technology, the system’s throughput can be improved a lot and the hidden-node problem can be alleviated greatly. Motivated by the envision of the Internet of lights, I study how to provide stable visible light links in VLC. I identify the limitations and tradeoff of two different types of optical receivers photodiode and LED, and design and implement a new optical data link layer that was resilient to dynamic environments. On the other hands, to meet the increasing demands, small cells are proposed and deployed in latest cellular networks. As a result, the number of users served by each cell is decreasing. As the opportunistic gain increases as a concave function of active users, in small cells and when dynamic traffic load are considered, the opportunistic gain will lost. To recoup the opportunistic gain, I propose a base-station transparent method based on D2D communication to dispatch traffic among devices. Dynamic programming is used to find the optimal dispatching policy. The results show this method can improve the average packet transfer delay greatly. To increase the opportunistic gain by a further step, I propose a base-station initiated policy to solve the same problem. An algorithm is therefore designed and implemented, and its performance shows that it can reduce the frame loss ratio significantly.This work has been supported by IMDEA Networks InstitutePrograma Oficial de Doctorado en Ingeniería TelemáticaPresidente: Thiemo Voigt.- Secretario: Pablo Serrano Yáñez-Mingot.- Vocal: David Malon

Quality-Oriented Mobility Management for Multimedia Content Delivery to Mobile Users

The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently we propose the Smooth Adaptive Soft-Handover Algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections. To estimate the capacity of each connection the novel Quality of Multimedia Streaming (QMS) metric is proposed. The QMS metric aims at offering maximum flexibility and efficiency allowing the applications to fine tune the behavior of the handover algorithm. The current simulation-based performance evaluation clearly shows the better performance of the proposed Smooth Adaptive Soft-Handover Algorithm as compared with other handover solutions. The evaluation was performed in various scenarios including multiple mobile hosts performing handover simultaneously, wireless networks with variable overlapping areas, and various network congestion levels

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications