Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Determining Additional Modulus of Subgarde Reaction Based on Tolerable Settlement for the Nailed-slab System Resting on Soft Clay.

Abstract—Nailed-slab System is a proposed alternative solution for rigid pavement problem on soft soils. Equivalent modulus of subgrade reaction (k’) can be used in designing of nailed-slab system. This modular is the cumulative of modulus of subgrade reaction from plate load test (k) and additional modulus of subgrade reaction due to pile installing (∆∆∆∆k). A recent method has used reduction of pile resistance approach in determining ∆∆∆∆k. The relative displacement between pile and soils, and reduction of pile resistance has been identified. In fact, determining of reduction of pile resistance is difficult. This paper proposes an approach by considering tolerable settlement of rigid pavement. Validation is carried out with respect to a loading test of nailed-slab models. The models are presented as strip section of rigid pavement. The theory of beams on elastic foundation is used to calculate the slab deflection by using k’. Proposed approach can results in deflection prediction close to observed one. In practice, the Nailed-slab System would be constructed by multiple-row piles. Designing this system based on one-pile row analysis will give more safety design and will consume less time

Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications

The use of computational intelligence for security in named data networking

Information-Centric Networking (ICN) has recently been considered as a promising paradigm for the next-generation Internet, shifting from the sender-driven end-to-end communication paradigma to a receiver-driven content retrieval paradigm. In ICN, content -rather than hosts, like in IP-based design- plays the central role in the communications. This change from host-centric to content-centric has several significant advantages such as network load reduction, low dissemination latency, scalability, etc. One of the main design requirements for the ICN architectures -since the beginning of their design- has been strong security. Named Data Networking (NDN) (also referred to as Content-Centric Networking (CCN) or Data-Centric Networking (DCN)) is one of these architectures that are the focus of an ongoing research effort that aims to become the way Internet will operate in the future. Existing research into security of NDN is at an early stage and many designs are still incomplete. To make NDN a fully working system at Internet scale, there are still many missing pieces to be filled in. In this dissertation, we study the four most important security issues in NDN in order to defense against new forms of -potentially unknown- attacks, ensure privacy, achieve high availability, and block malicious network traffics belonging to attackers or at least limit their effectiveness, i.e., anomaly detection, DoS/DDoS attacks, congestion control, and cache pollution attacks. In order to protect NDN infrastructure, we need flexible, adaptable and robust defense systems which can make intelligent -and real-time- decisions to enable network entities to behave in an adaptive and intelligent manner. In this context, the characteristics of Computational Intelligence (CI) methods such as adaption, fault tolerance, high computational speed and error resilient against noisy information, make them suitable to be applied to the problem of NDN security, which can highlight promising new research directions. Hence, we suggest new hybrid CI-based methods to make NDN a more reliable and viable architecture for the future Internet.Information-Centric Networking (ICN) ha sido recientemente considerado como un paradigma prometedor parala nueva generación de Internet, pasando del paradigma de la comunicación de extremo a extremo impulsada por el emisora un paradigma de obtención de contenidos impulsada por el receptor. En ICN, el contenido (más que los nodos, como sucede en redes IPactuales) juega el papel central en las comunicaciones. Este cambio de "host-centric" a "content-centric" tiene varias ventajas importantes como la reducción de la carga de red, la baja latencia, escalabilidad, etc. Uno de los principales requisitos de diseño para las arquitecturas ICN (ya desde el principiode su diseño) ha sido una fuerte seguridad. Named Data Networking (NDN) (también conocida como Content-Centric Networking (CCN) o Data-Centric Networking (DCN)) es una de estas arquitecturas que son objetode investigación y que tiene como objetivo convertirse en la forma en que Internet funcionará en el futuro. Laseguridad de NDN está aún en una etapa inicial. Para hacer NDN un sistema totalmente funcional a escala de Internet, todavía hay muchas piezas que faltan por diseñar. Enesta tesis, estudiamos los cuatro problemas de seguridad más importantes de NDN, para defendersecontra nuevas formas de ataques (incluyendo los potencialmente desconocidos), asegurar la privacidad, lograr una alta disponibilidad, y bloquear los tráficos de red maliciosos o al menos limitar su eficacia. Estos cuatro problemas son: detección de anomalías, ataques DoS / DDoS, control de congestión y ataques de contaminación caché. Para solventar tales problemas necesitamos sistemas de defensa flexibles, adaptables y robustos que puedantomar decisiones inteligentes en tiempo real para permitir a las entidades de red que se comporten de manera rápida e inteligente. Es por ello que utilizamos Inteligencia Computacional (IC), ya que sus características (la adaptación, la tolerancia a fallos, alta velocidad de cálculo y funcionamiento adecuado con información con altos niveles de ruido), la hace adecuada para ser aplicada al problema de la seguridad ND

A metaheuristic and simheuristic approach for the p-Hub median problem from a telecommunication perspective

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.Avanços recentes no setor das telecomunicações oferecem grandes oportunidades para cidadãos e organizações em um mundo globalmente conectado, ao mesmo tempo em que surge um vasto número de desafios complexos que os engenheiros devem enfrentar. Alguns desses desafios podem ser modelados como problemas de otimização. Alguns exemplos incluem o problema de alocação de recursos em redes de comunicações, desenho de topologias de rede que satisfaça determinadas propriedades associadas a requisitos de qualidade de serviço, sobreposição de redes multicast e outros recursos importantes para comunicação de origem a destino. O primeiro objetivo desta tese é fornecer uma revisão sobre como as metaheurísticas têm sido usadas até agora para lidar com os problemas de otimização associados aos sistemas de telecomunicações, detectando as principais tendências e desafios. Particularmente, a análise enfoca os problemas de desenho, roteamento e alocação de recursos. Além disso, devido á natureza desses desafios, o presente trabalho discute como a hibridização de metaheurísticas com metodologias como simulação pode ser empregada para ampliar as capacidades das metaheurísticas na resolução de problemas de otimização estocásticos na indústria de telecomunicações. Logo, é analisado um problema de otimização com aplicações práticas para redes de telecomunica ções: o problema das p medianas não capacitado em que um número fixo de hubs tem capacidade ilimitada, cada nó não-hub é alocado para um único hub e o número de hubs é conhecido de antemão, sendo analisado em cenários determinísticos e estocásticos. Dada a sua variedade e importância prática, o problema das p medianas vem sendo aplicado e estudado em vários contextos. Seguidamente, propõem-se dois algoritmos imune-inspirados e uma metaheurística de dois estágios, que se baseia na combinação de técnicas tendenciosas e aleatórias com uma estrutura de busca local iterada, além de sua integração com a técnica de simulação de Monte Carlo para resolver o problema das p medianas. Para demonstrar a eficiência dos algoritmos, uma série de testes computacionais é realizada, utilizando instâncias de grande porte da literatura. Estes resultados contribuem para uma compreensão mais profunda da eficácia das metaheurísticas empregadas para resolver o problema das p medianas em redes pequenas e grandes. Por último, uma aplicaçã o ilustrativa do problema das p medianas é apresentada, bem como alguns insights sobre novas possibilidades para ele, estendendo a metodologia proposta para ambientes da vida real.Recent advances in the telecommunication industry o er great opportunities to citizens and organizations in a globally-connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as optimization problems. Examples include the framework of network utility maximization for resource allocation in communication networks, nding a network topology that satis es certain properties associated with quality of service requirements, overlay multicast networks, and other important features for source to destination communication. First, this thesis provides a review on how metaheuristics have been used so far to deal with optimization problems associated with telecommunication systems, detecting the main trends and challenges. Particularly the analysis focuses on the network design, routing, and allocation problems. In addition, due to the nature of these challenges, this work discusses how the hybridization of metaheuristics with methodologies such as simulation can be employed to extend the capabilities of metaheuristics when solving stochastic optimization problems. Then, a popular optimization problem with practical applications to the design of telecommunication networks: the Uncapacitated Single Allocation p-Hub Median Problem (USApHMP) where a xed number of hubs have unlimited capacity, each non-hub node is allocated to a single hub and the number of hubs is known in advance is analyzed in deterministic and stochastic scenarios. p-hub median problems are concerned with optimality of telecommunication and transshipment networks, and seek to minimize the cost of transportation or establishing. Next, two immune inspired metaheuristics are proposed to solve the USApHMP, besides that, a two-stage metaheuristic which relies on the combination of biased-randomized techniques with an iterated local search framework and its integration with simulation Monte Carlo technique for solving the same problem is proposed. In order to show their e ciency, a series of computational tests are carried out using small and large size instances from the literature. These results contribute to a deeper understanding of the e ectiveness of the employed metaheuristics for solving the USApHMP in small and large networks. Finally, an illustrative application of the USApHMP is presented as well as some insights about some new possibilities for it, extending the proposed methodology to real-life environments.Els últims avenços en la industria de les telecomunicacions ofereixen grans oportunitats per ciutadans i organitzacions en un món globalment connectat, però a la vegada, presenten reptes als que s'enfronten tècnics i enginyers que prenen decisions. Alguns d'aquests reptes es poden modelitzar com problemes d'optimització. Exemples inclouen l'assignació de recursos a les xarxes de comunicació, trobant una topologia de xarxa que satisfà certes propietats associades a requisits de qualitat de servei, xarxes multicast superposades i altres funcions importants per a la comunicació origen a destinació. El primer objectiu d'aquest treball és proporcionar un revisió de la literatura sobre com s'han utilitzat aquestes tècniques, tradicionalment, per tractar els problemes d'optimització associats a sistemes de telecomunicació, detectant les principals tendències i desa aments. Particularment, l'estudi es centra en els problemes de disseny de xarxes, enrutament i problemes d'assignació de recursos. Degut a la naturalesa d'aquests problemes, aquest treball també analitza com es poden combinar les tècniques metaheurístiques amb metodologies de simulació per ampliar les capacitats de resoldre problemes d'optimització estocàstics. A més, es tracta un popular problema d'optimització amb aplicacions pràctiques per xarxes de telecomunicació, el problema de la p mediana no capacitat, analitzant-lo des d'escenaris deterministes i estocàstics. Aquest problema consisteix en determinar el nombre d'instal lacions (medianes) en una xarxa, minimitzant la suma de tots els costs o distàncies des d'un punt de demanda a la instal lació més propera. En general, el problema de la p mediana està lligat amb l'optimització de xarxes de telecomunicacions i de transport, i busquen minimitzar el cost de transport o establiment de la xarxa. Es proposa dos algoritmes immunològics i un algoritme metaheurístic de dues etapes basat en la combinació de tècniques aleatòries amb simulacions Monte Carlo. L'e ciència de les algoritmes es posa a prova mitjançant alguns dels test computacionals més utilitzats a la literatura, obtenint uns resultats molt satisfactoris, ja que es capaç de resoldre casos petits i grans en qüestió de segons i amb un baix cost computacional. Finalment, es presenta una aplicació il lustrativa del problema de la p mediana, així com algunes noves idees sobre aquest, que estenen la metodologia proposta a problemes de la vida real

A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics

The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. Because of that, in spite of the fact that there are a lot of surveys and reviews in the field, they quickly become dated. Thus, it is of importance to keep pace with the current developments. In this review, we first consider a possible classification of bio-inspired multiparameter optimization methods because papers dedicated to that area are relatively scarce and often contradictory. We proceed by describing in some detail some more prominent approaches, as well as those most recently published. Finally, we consider the use of biomimetic algorithms in two related wide fields, namely microelectronics (including circuit design optimization) and nanophotonics (including inverse design of structures such as photonic crystals, nanoplasmonic configurations and metamaterials). We attempted to keep this broad survey self-contained so it can be of use not only to scholars in the related fields, but also to all those interested in the latest developments in this attractive area

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems