Generation Internet Of Things Research Articles

On the Usability of a Modeling Language for IoT-Based Public Transportation Systems

Internet of Things (IoT)-based public transportation systems face distinct challenges within the broader realm of IoT. Developers of such systems encounter a notably intricate development environment compared to general IoT systems, which are inherently characterized by elevated levels of complexity and heterogeneity. As successfully applied in other domains, domain-specific modeling languages (DSMLs) can also be employed to facilitate the development of IoT-based public transportation systems and address the challenges mentioned. Hence, in this study, a novel model-driven engineering (MDE) methodology is presented, comprising the steps of using a DSML, called DSML4PT, for the development of a wide-range of IoT-based public transportation applications. Moreover, the usability evaluation of DSML4PT within this MDE methodology during the real applications of IoT-based public transportation systems is also provided, which is missing in similar studies. For this purpose, we investigated the usability of DSML4PT within a systematic evaluation approach in which the features of DSML4PT are assessed both quantitatively and qualitatively in eight different real public transportation applications with the participation of experienced developers. Comparative analysis revealed that approximately 80% of IoT-based public transportation systems could be automatically generated through modeling exclusively employing DSML4PT. In contrast to the conventional software development methodologies, the novel DSML4PT approach also decreased the time required for the development of public transportation applications by almost 50%. In addition, according to a questionnaire-based assessment, the general evaluation rating of the language was measured as 4.44 over 5-point Likert scale. Feedback from the developers corroborated the practicality of this language and its widespread adoption across diverse perspectives.

5G IoT Networks

The abstract delves into how the advent of 5G is revolutionizing the Internet of Things (IoT) across various industries, with a particular focus on its ability to provide ultra-low latency, high data rates, and support for a massive number of connected devices, enabling real-time data transmission. It highlights the mutually beneficial relationship between 5G and IoT, which is driving innovation in sectors such as smart cities, healthcare, agriculture, and transportation. The abstract also addresses important challenges like security and interoperability, emphasizing the need for strategic deployment of 5G-enabled IoT solutions. Furthermore, it explores the potential of edge computing and AI-driven analytics to unlock new possibilities in IoT implementations. In summary, the abstract underscores the transformative power of 5G in shaping IoT ecosystems, offering unparalleled opportunities for innovation, efficiency, and value creation.

Interoperability Structure of Smart Water Conservancy Based on Internet of Things

Massive smart water conservancy object (WCO) need to be connected for real-time monitoring and control, which produces massive data. Unfortunately, heterogeneous data structures and semantics lead to low interoperability between WCO and management systems. To address this challenge, we propose a novel interoperability structure for a smart water conservancy system based on the Internet of Things (IoT), and the key design includes a smart WCO terminal, interoperability network, special interoperability protocol, WCO information model, and cloud platform. Universal terminal and network are the base of interoperability hardware, and special interoperability protocol and information model for interconnection of WCO are designed for smart water conservancy management system. WCO can be connected to a water conservancy Big Data processing cloud platform for interoperability applications. The application results demonstrate that our proposed WCO’s interoperability structure has obvious advantages than the general IoT at WCO interoperability. The interoperability protocol is reliable, the information model can ease interoperability and security, and the semantic dictionary is very rich and covers all semantic services of WCO.

Driving innovation in energy and telecommunications: next-generation energy storage and 5G technology for enhanced connectivity and energy solutions

Driving innovation in energy and telecommunications involves leveraging next-generation energy storage and 5G technology to enhance connectivity and energy solutions. This review explores the intersection of these two domains, highlighting the importance of advancements in energy storage and 5G technology for a sustainable and connected future. Energy storage is crucial for balancing the supply and demand of electricity in modern power systems. Traditional energy storage methods, such as batteries and pumped hydro, have limitations in terms of scalability, efficiency, and cost-effectiveness. Next-generation energy storage technologies, including advanced batteries, hydrogen storage, and thermal storage, offer promising solutions to overcome these limitations. These technologies enable efficient energy storage at scale, facilitating the integration of renewable energy sources like solar and wind into the grid. By storing excess energy generated during periods of low demand, next-generation energy storage systems ensure a reliable and stable power supply, reducing the reliance on fossil fuels and lowering greenhouse gas emissions. In parallel, the evolution of telecommunications technology, particularly the advent of 5G networks, is revolutionizing connectivity and communication. 5G technology offers significantly higher data transfer speeds, lower latency, and increased network capacity compared to its predecessors. These capabilities are essential for supporting emerging technologies such as the Internet of Things (IoT), autonomous vehicles, and smart grids. With 5G-enabled IoT devices, utilities can monitor energy consumption in real-time, optimize grid operations, and detect and respond to faults more efficiently. Moreover, 5G connectivity enhances the efficiency and reliability of energy storage systems by enabling seamless communication between distributed energy resources and grid operators. The convergence of next-generation energy storage and 5G technology presents numerous opportunities for driving innovation in both energy and telecommunications sectors. One of the key areas of innovation is the development of smart energy storage systems equipped with 5G connectivity. These systems can autonomously adjust their operation based on grid conditions, weather forecasts, and energy demand patterns, optimizing energy storage and distribution in real-time. Furthermore, advanced energy management algorithms leveraging artificial intelligence (AI) and machine learning (ML) algorithms can optimize energy usage and storage, further improving the efficiency and reliability of the grid. Another area of innovation lies in the integration of renewable energy resources with 5G-enabled microgrids. Microgrids are localized energy systems that can operate independently or in conjunction with the main grid. By combining renewable energy sources with energy storage and 5G-enabled communication, microgrids can provide reliable, clean, and resilient power to remote or urban areas. These microgrids can also facilitate peer-to-peer energy trading, allowing consumers to buy and sell excess energy within their communities, fostering energy independence and sustainability. Furthermore, advancements in battery technology, such as solid-state batteries and flow batteries, are enhancing the performance and reliability of energy storage systems. Solid-state batteries offer higher energy density, faster charging rates, and improved safety compared to conventional lithium-ion batteries. Flow batteries, on the other hand, provide scalability and long-duration storage capabilities, making them suitable for grid-scale applications. Integrating these advanced battery technologies with 5G-enabled monitoring and control systems enhances the overall resilience and flexibility of the energy infrastructure. In addition to technological advancements, driving innovation in energy and telecommunications requires collaboration among various stakeholders, including policymakers, regulators, industry players, and research institutions. Policies and regulations should incentivize the deployment of next-generation energy storage and 5G infrastructure, promote interoperability standards, and ensure data privacy and security. Public-private partnerships can facilitate the investment and deployment of innovative solutions, while research and development initiatives can spur further technological advancements. Driving innovation in energy and telecommunications through next-generation energy storage and 5G technology is essential for building a sustainable, connected, and resilient future. By leveraging advanced energy storage systems, smart grids, and 5G-enabled communication networks, we can optimize energy usage, reduce carbon emissions, and enhance the reliability and efficiency of our energy infrastructure. Collaboration and investment across various sectors are key to unlocking the full potential of these transformative technologies and achieving a brighter, more sustainable future for generations to come. Keywords: Innovation, Energy, Telecommunications, Next-Generation, 5G technology, Enhanced connectivity.

Analyzing the suitability of IEEE 802.11ah for next generation Internet of Things: A comparative study

Hyperconnectivity, real-time processing, and interoperable communication facilities are key to the Next Generation (NG) Internet of Things (IoT). However, existing IoT architectures employ a diverse range of communication technologies to support desired data rates and coverage range, making them more complex to manage. The emerging IEEE 802.11ah standard, marketed as WiFi HaLow™, enables seamless communication among large-scale and energy-efficient sensor/actuator nodes to the Internet. IEEE 802.11ah introduces key features like Restricted Access Window (RAW) for reducing contention, Hierarchical Traffic Indication Map (TIM) and Association Identifier (AID) for efficient scheduling and device identification, and multiple Modulation and Coding Schemes (MCSs) for adaptive data transmission, enhancing IoT connectivity in Next-Generation IoT (NGI) communication. In this paper, we discuss IEEE 802.11ah for NGI concerning different requirements in terms of communication and computation. We survey the suitability of 802.11ah for NGI as compared to the existing state-of-the-art connectivity solutions. Thereafter, an IEEE 802.11ah-based NGI architecture and protocol stack are proposed and discussed, according to the different distinct features of this novel technology. Finally, we conclude by enumerating research and future directions for the proposed network architecture.

Generic IoT for Smart Buildings and Field-Level Automation—Challenges, Threats, Approaches, and Solutions

Smart home and building systems are popular solutions that support maintaining comfort and safety and improve energy efficiency in buildings. However, dynamically developing distributed network technologies, in particular the Internet of Things (IoT), are increasingly entering the above-mentioned application areas of building automation, offering new functional possibilities. The result of these processes is the emergence of many different solutions that combine field-level and information and communications technology (ICT) networks in various configurations and architectures. New paradigms are also emerging, such as edge and fog computing, providing support for local monitoring and control networks in the implementation of advanced functions and algorithms, including machine learning and artificial intelligence mechanisms. This paper collects state-of-the-art information in these areas, providing a systematic review of the literature and case studies with an analysis of selected development trends. The author systematized this information in the context of the potential development of building automation systems. Based on the conclusions of this analysis and discussion, a framework for the development of the Generic IoT paradigm in smart home and building applications has been proposed, along with a strengths, weaknesses, opportunities, and threats (SWOT) analysis of its usability. Future works are proposed as well.

Enhancing Security of 5G-Enabled IoT Systems through Advanced Authentication Mechanisms: A Multifaceted Approach

The Internet of Things (IoT) has revolutionized communication among devices, offering unprecedented efficiency and convenience. However, the widespread adoption of IoT has raised significant security concerns, emphasizing the need for robust security measures. This study focuses on the crucial aspect of authentication within the layered architecture of IoT systems. Authentication is foundational to the architecture, ensuring the availability, security, and integrity of IoT services and data. The research evaluates the current state of IoT authentication techniques, highlighting limitations in conventional solutions. To address these shortcomings, an advanced authentication framework is proposed, incorporating cutting-edge technologies such as blockchain, artificial intelligence, and biometrics. The framework employs biometric data for a dynamic and adaptive authentication process, enhancing security and accuracy in user and device identification. Blockchain technology is integrated to establish a decentralized and tamper-resistant identity management system, reducing the risk of unauthorized access and data manipulation. Artificial intelligence continuously adapts authentication processes based on behavioural patterns, bolstering the system's resilience against evolving cyber threats. The study also discusses the practical application of the proposed authentication system, considering resource limitations in IoT devices. It provides insights into the efficiency, scalability, and interoperability of the suggested solution within various IoT ecosystems. The research contributes to the ongoing discourse on IoT security by thoroughly examining enhanced authentication procedures. Organizations can fortify their IoT deployments against a growing array of cyber threats by prioritizing advanced authentication within a layered design, fostering a more secure and reliable IoT ecosystem. Additionally, the study presents a comprehensive overview of the state-of-the-art security in IoT, exploring various designs, enabling technologies, and protocols. It delves into security challenges at each architectural tier, providing an in-depth analysis of attack taxonomies and advanced defenses. The article serves as a valuable resource for researchers and academics in the IoT sector, offering a detailed survey of architectural security, identification of challenges, resolution strategies, and insights into the evolving landscape of IoT. The study provides a comprehensive survey of IoT architectural security, identifying challenges, proposing resolutions, and highlighting changes in the IoT domain. This research aims to enhance the accuracy by 80% of IoT security, fostering a more secure and reliable IoT ecosystem.

Optimal D2D power for secure D2D communication with random eavesdropper in 5G‐IoT networks

SummaryIn the rapidly evolving landscape of fifth generation Internet of Things (5G‐IoT) networks, Device‐to‐Device (D2D) communication has emerged as a promising paradigm to enhance secrecy transmission rate (STR) and connectivity. However, the security of D2D communications in the presence of eavesdroppers remains a critical challenge. This article investigates the problem of optimizing D2D transmit power to achieve secure D2D communication while considering the presence of random eavesdroppers in 5G‐IoT networks. We propose a novel secrecy‐based power control approach (SRMWPCA) approach to model the random distribution of eavesdroppers in the network, taking into account their varying distances from D2D pairs and deliberately increasing interference at the eavesdropper's link. By leveraging tools from stochastic geometry, we derive an analytical expression for the secrecy transmission probability (STP), which quantifies the probability of eavesdroppers successfully decoding the D2D transmission. In this analysis, we have incorporated practical considerations such as channel fading, path loss, and interference from other devices. To enhance the security of D2D communication, we formulate an optimization problem to determine the optimal transmit power levels for D2D pairs, subject to constraints on the secrecy transmission probability and interference to the cellular network. We propose an efficient algorithm to find the power allocation that maximizes the secrecy outage performance while meeting these constraints. Simulation results demonstrate the effectiveness of the proposed approach in achieving secure D2D communication in 5G‐IoT networks with random eavesdroppers. The performance of the proposed SRMWPCA approach improved by 23.25% and 20.9% compared with standard approaches in terms of the secrecy rate and throughput of the users from malicious attacks.

A Millimeter-Wave Wideband Antenna Module With Switchable Fan-Beam Radiation for Wide Coverage of 5G IoT Applications

Millimeter wave (mm-wave) antenna modules with switchable beam radiation provide a potential solution for enabling flexible wireless links and high data rate in Internet of Things (IoT) networks. Aiming to simultaneously fulfill a wide coverage and follow the cost-effective principle of IoT devices, a novel mm-wave wideband antenna module with switchable fanbeam radiation is proposed based on an air-filled planar Cassegrain beam-former. A comprehensive design procedure combing the theoretical calculation and differential evolution (DE) algorithm is first introduced to construct the beam-former with wide-angle scanning capability. The desirable apertureshared switchable fan-beam radiation with high crossover is then obtained with the aid of a proposed two-feed-per-beam (2FPB) scheme based on a low-loss integrated switch network. A prototype of the antenna in the Ka-band is fabricated by simultaneously adopting the metallic three-dimensional (3D) printing and printed circuit board (PCB) technology. Excellent operating characteristics, including a wide bandwidth of more than 32%, twenty stable fan-shaped radiation beams scanning over a wide angular range of ±45∘ in the H-plane, a high beam crossover of about -3 dB, a gain of up to 19.6 dBi, and a radiation efficiency of greater than 80% are demonstrated experimentally. With the ability to fulfill the radio coverage within a wide conical area, the presented antenna module would be an attractive candidate for the fifth generation (5G) IoT applications.

Optimal Pricing Design for Coordinated and Uncoordinated IoT Networks

An Internet of Things (IoT) system can include several different types of service providers, who sell IoT service, network service, and computation service to customers, either jointly or separately. A deep understanding of complicated coupling among these providers in terms of pricing and service decisions is critical to the success of IoT networks. This paper studies the impact of the provider interaction structures on the overall IoT system with heterogeneous customers. Specifically, we first study a generic IoT scenario with three interaction structures: coordinated, vertically-uncoordinated, and horizontally-uncoordinated structures. Despite the challenging non-convex optimization problems involved in modeling and analyzing these structures, we successfully obtain the closed-form optimal pricing strategies of providers in each interaction structure. We further extend the analysis to a specific IoT scenario with local computation capability (e.g., Internet of Vehicles (IoV)). We prove that the coordinated structure is better than two uncoordinated structures for both providers and customers, as it avoids selfish price markup behaviors in uncoordinated structures. Between the two uncoordinated structures, when customers' demand variance is large and utility-cost ratio is medium, vertically-uncoordinated structure is better than horizontal one for both providers and customers, due to the complementary providers' competition in horizontally-uncoordinated structure. Counter-intuitively, we identify that providers' optimal prices do not change with their costs at the critical point of customers' full participation in the vertically-uncoordinated structure.

SECURE TEXT ENCRYPTION FOR IOT COMMUNICATION USING AFFINE CIPHER AND DIFFIE-HELLMAN KEY DISTRIBUTION ON ARDUINO ATMEGA2560 IOT DEVICES

In an Internet of Things (IoT) system, devices connected to the system exchange data. The data contains sensitive information about the connected devices in the system so it needs to be protected. Without security, the data in the IoT system can be easily retrieved. One way to prevent this is by implementing cryptography. Cryptography is a technique for protecting information by using encryption so that only the sender and receiver can see the contents of the information contained therein. The implementation of cryptography on IoT devices must consider the capabilities of IoT devices because in general IoT devices have limited processing capabilities compared to computer devices. Therefore, the selection of encryption algorithms needs to be adjusted to the computational capabilities of IoT devices. In this research, the affine cipher cryptography algorithm and Diffie-hellman key distribution algorithm are applied to the arduino atmega2560 IoT device. The purpose of this research is to increase the security of the IoT system by implementing cryptography. The method used in this research involves setting up a sequence of encryption and decryption steps using an affine cipher and diffie-hellman algorithms. Furthermore, these algorithms were implemented on an Arduino IoT device. Finally, the decryption time based on the number of characters and the avalanche test were tested. The results showed that on average, Arduino can perform decryption using affine cipher and diffie-hellman algorithms in 0.07 milliseconds per character. The avalanche test produced an average percentage of 45.51% from five trials.

Chained Packets for Multimedia Random Access in Next Generation Internet of Things

Chained Packets for Multimedia Random Access in Next Generation Internet of Things

Survey: An Overview of Lightweight RFID Authentication Protocols Suitable for the Maritime Internet of Things

The maritime sector employs the Internet of Things (IoT) to exploit many of its benefits to maintain a competitive advantage and keep up with the growing demands of the global economy. The maritime IoT (MIoT) not only inherits similar security threats as the general IoT, it also faces cyber threats that do not exist in the traditional IoT due to factors such as the support for long-distance communication and low-bandwidth connectivity. Therefore, the MIoT presents a significant concern for the sustainability and security of the maritime industry, as a successful cyber attack can be detrimental to national security and have a flow-on effect on the global economy. A common component of maritime IoT systems is Radio Frequency Identification (RFID) technology. It has been revealed in previous studies that current RFID authentication protocols are insecure against a number of attacks. This paper provides an overview of vulnerabilities relating to maritime RFID systems and systematically reviews lightweight RFID authentication protocols and their impacts if they were to be used in the maritime sector. Specifically, this paper investigates the capabilities of lightweight RFID authentication protocols that could be used in a maritime environment by evaluating those authentication protocols in terms of the encryption system, authentication method, and resistance to various wireless attacks.

Enhancing Data Security in IoT Networks with Blockchain-Based Management and Adaptive Clustering Techniques

The rapid proliferation of smart devices in Internet of Things (IoT) networks has amplified the security challenges associated with device communications. To address these challenges in 5G-enabled IoT networks, this paper proposes a multi-level blockchain security architecture that simplifies implementation while bolstering network security. The architecture leverages an adaptive clustering approach based on Evolutionary Adaptive Swarm Intelligent Sparrow Search (EASISS) for efficient organization of heterogeneous IoT networks. Cluster heads (CH) are selected to manage local authentication and permissions, reducing overhead and latency by minimizing communication distances between CHs and IoT devices. To implement network changes such as node addition, relocation, and deletion, the Network Efficient Whale Optimization (NEWO) algorithm is employed. A localized private blockchain structure facilitates communication between CHs and base stations, providing an authentication mechanism that enhances security and trustworthiness. Simulation results demonstrate the effectiveness of the proposed clustering algorithm compared to existing methodologies. Overall, the lightweight blockchain approach presented in this study strikes a superior balance between network latency and throughput when compared to conventional global blockchain systems. Further analysis of system under test (SUT) behavior was accomplished by running many benchmark rounds at varying transaction sending speeds. Maximum, median, and lowest transaction delays and throughput were measured by generating 1000 transactions for each benchmark. Transactions per second (TPS) rates varied between 20 and 500. Maximum delay rose when throughput reached 100 TPS, while minimum latency maintained a value below 1 s.

Tactile internet of federated things: Toward fine-grained design of FL-based architecture to meet TIoT demands

The Tactile Internet of Things (TIoT) represents a special class of the Internet of Things (IoT) that has opened the door for a new generation of agile, highly dynamic, intelligent, and bandwidth-hungry applications in many vital domains such as medical, military, robotics, and entertainment. However, the TIoT’s high level of physical requirements constitute a challenge that hinders the technology’s full potential. The application of machine learning (ML) methods has become of high importance to facilitate the prolific deployment of TIoT devices and applications. Along with advances in 6G and networking-enabling technologies, federated learning (FL) can bridge this gap by boosting TIoT services due to its inherent and redundant distributed nature. To the best of our knowledge, no other work in the literature covers applications of FL in the TIoT. In this work, we identify the prospective approach with a final aim of finding an appropriate architecture for the TIoT based on FL as we survey, compare, and analyze recent literature. We conducted a comprehensive and in-depth study of FL design aspects relevant to the deployment of the TIoT and suggested categorization of these aspects into process, infrastructure, data, enabler, and defense classes. On the other hand, as we are seeking to define a role for FL in the TIoT, we identified services of ML in the IoT domain as a general case of the FL/TIoT special case. Moreover, the shortcomings of traditional ML in regard to the general IoT are highlighted. We find that FL can be replaced, especially in the case of the TIoT, to meet the high level of design constraints. Eventually, we draw conclusions and future directions of common challenges relevant to applying FL in the domain of the TIoT.

Multi-agent reinforcement learning enabled link scheduling for next generation Internet of Things

In next generation Internet of Things (NG-IoT) networks, numerous pieces of information are aggregated from the user devices and sensor nodes to the local computing units for further computing to support high-level applications. Those multitudinous transmission demands have raised new challenges for current link scheduling protocols. The centralized link scheduling protocols are inappropriate in some large-scale NG-IoT scenarios. The previously distributed link scheduling uses the randomized transmission scheme to avoid interference, making it hard to utilize the bandwidth resources fully. The multi-agent machine learning (MAML) technique is a potential approach to finding the most optimal link scheduling strategy. At the same time, the over-large state space will take a long time for them to approach the optimal solution, which reduces the practicality of the MAML. To fully utilize the bandwidth resource and improve the efficiency of link scheduling, this paper studies a multi-agent reinforcement learning enabled link scheduling problem. Different from the conventional MAML techniques that randomly select a state to do their exploration, in our multi-agent reinforcement learning algorithm, a good state is firstly obtained within polynomial time steps by executing a distributed and randomized sub-algorithm. We say a state is good if it is not far from the optimal state. Then, our multi-agent reinforcement learning scheme starts from the good state and does its exploration with an ɛ greedy scheme, which significantly reduces the time steps to get close to the optimal link scheduling strategy. Extensive simulations are conducted to investigate the performance of our work.

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse.

Global concerns regarding environmental preservation and energy sustainability have emerged due to the various impacts of constantly increasing energy demands and climate changes. With advancements in smart grid, edge computing, and Metaverse-based technologies, it has become apparent that conventional private power networks are insufficient to meet the demanding requirements of industrial applications. The unique capabilities of 5G, such as numerous connections, high reliability, low latency, and large bandwidth, make it an excellent choice for smart grid services. The 5G network industry will heavily rely on the Internet of Things (IoT) to progress, which will act as a catalyst for the development of the future smart grid. This comprehensive platform will not only include communication infrastructure for smart grid edge computing, but also Metaverse platforms. Therefore, optimizing the IoT is crucial to achieve a sustainable edge computing network. This paper presents the design, fabrication, and evaluation of a super-efficient GSM triplexer for 5G-enabled IoT in sustainable smart grid edge computing and the Metaverse. This component is intended to operate at 0.815/1.58/2.65 GHz for 5G applications. The physical layout of our triplexer is new, and it is presented for the first time in this work. The overall size of our triplexer is only 0.007 λg2, which is the smallest compared to the previous works. The proposed triplexer has very low insertion losses of 0.12 dB, 0.09 dB, and 0.42 dB at the first, second, and third channels, respectively. We achieved the minimum insertion losses compared to previous triplexers. Additionally, the common port return losses (RLs) were better than 26 dB at all channels.

A High-Efficiency Diplexer for Sustainable 5G-Enabled IoT in Metaverse Transportation System and Smart Grids

Symmetry is essential in the design of complex systems like the Metaverse Transportation Sys-tem (MTS) and helps ensure that all components work together effectively. In the development of a microstrip diplexer for 5G-enabled IoT and MTS, maintaining symmetry is crucial to achieving flat responses with low group delays. By integrating transportation technology and the Metaverse, the Metaverse Transportation System (MTS) can greatly improve the effectiveness and intellect of transportation systems in reality. To establish a dependable network, it is essential to include 5G-enabled Internet of Things (IoT) and sensor networks with a sustainable design that focuses on efficiency and energy conservation. A three-channel microstrip lowpass-bandpass diplexer has been developed for 5G-enabled IoT and MTS implementation. Multi-channel designs are rare due to the complex design process, but this diplexer is very compact at only 0.004 λg2. All channels have flat responses with group delays of 0.34 ns, 1.7 ns, and 0.34 ns at the lower, middle, and upper passbands, respectively. The lowpass channel has a cut-off frequency of 1.22 GHz, suitable for mid-band 5G applications. Compared to previous work, this diplexer achieves the smallest size, lowest group delay, and insertion and return losses at the lower channel. It consists of a lowpass-bandpass section connected to a band-pass filter analyzed mathematically, and its performance has been verified through simulation and measurement with good accuracy.

ASSIST-IoT: A Modular Implementation of a Reference Architecture for the Next Generation Internet of Things

Next Generation Internet of Things (NGIoT) addresses the deployment of complex, novel IoT ecosystems. These ecosystems are related to different technologies and initiatives, such as 5G/6G, AI, cybersecurity, and data science. The interaction with these disciplines requires addressing complex challenges related with the implementation of flexible solutions that mix heterogeneous software and hardware, while providing high levels of customisability and manageability, creating the need for a blueprint reference architecture (RA) independent of particular existing vertical markets (e.g., energy, automotive, or smart cities). Different initiatives have partially dealt with the requirements of the architecture. However, the first complete, consolidated NGIoT RA, covering the hardware and software building blocks, and needed for the advent of NGIoT, has been designed in the ASSIST-IoT project. The ASSIST-IoT RA delivers a layered and modular design that divides the edge-cloud continuum into independent functions and cross-cutting capabilities. This contribution discusses practical aspects of implementation of the proposed architecture within the context of real-world applications. In particular, it is shown how use of cloud-native concepts (microservices and applications, containerisation, and orchestration) applied to the edge-cloud continuum IoT systems results in bringing the ASSIST-IoT concepts to reality. The description of how the design elements can be implemented in practice is presented in the context of an ecosystem, where independent software packages are deployed and run at the selected points in the hardware environment. Both implementation aspects and functionality of selected groups of virtual artefacts (micro-applications called enablers) are described, along with the hardware and software contexts in which they run.

5G-Enabled Cyber-Physical Systems for Smart Transportation Using Blockchain Technology

The physical world can be controlled directly over the Internet once a Cyber-Physical 1 System (CPS) infrastructure is established. The Intelligent Transportation System (ITS) encompasses Wireless Sensor Network (WSN), Vehicular ad hoc network (VANET), and 5G-enabled Internet of Things (IoT) solutions to transform traditional transportation into an ITS. This research investigates the option of running a blockchain-driven security assurance model to safeguard intelligent roads and smart vehicles as part of ITS. The proposed model considers a semi-distributed model in blockchain deployment to ensure satisfactory Internet of Vehicles (IoV) service while mining acceptable security assurance. The experimental outcomes on intelligent roads and smart parking management indicate that the proposed model achieves comparably good data delivery and reduced latency, paving the way to an innovative deployment of blockchain technologies in IoV for a dependable and trustworthy ITS.