Communication Network Architecture Research Articles

Key Issues on Integrating 5G into Industrial Systems

Under the auspice of further developing 5G mobile communication technology and integrating it with the latest advancements in the field of Industrial Internet-of-Things, this study conducts in-depth research and detailed analysis on the combination of 5G with industrial systems based on composite structures, communication network architectures, wireless application scenarios, and communication protocols. The status quo, development trend, and necessity of 5G mobile communication technology are explored and its potential in industrial applications is analyzed. Based on the current practical development level of 5G technology, by considering different requirements for bandwidth, real-time performance, and reliability in communication networks of industrial systems, this study proposes three feasible paths for the integration between 5G and industrial systems, including the method to use 5G in place of field buses. Finally, by introducing real-world cases, this study has successfully demonstrated the integration of 5G and industrial systems by extending 5G terminals as field bus gateways. This study provides valuable references for research and practice in related fields.

QoS prediction using EMD-BiLSTM for II-IoT-secure communication systems

Abstract To address the challenges of secure and reliable communication and system quality of service (QoS) prediction in intelligent production lines (IPL) in the Industrial Intelligent Internet of Things (II-IOT) environment, a redundant collaborative security model-based communication architecture is designed. First, the redundant collaborative security communication model is introduced to construct the network communication architecture of IPL, including the industrial-site mechanical floor, data awareness layer, and gateway and application layer. Then, to leverage the advantages of the empirical-mode decomposition (EMD) method and the bidirectional long short-term memory (BiLSTM) model in time-series data analysis and processing, an EMD-BiLSTM-based QoS prediction model is proposed that can synchronously achieve one-step and multi-step prediction of QoS attributes. The proposed model exhibits a prediction accuracy of up to 94.01% on the SourceForge dataset, with prediction, recall, and F1 values as high as 91.37, 90.60, and 90.99%, respectively. The proposed EMD-BiLSTM model can achieve better performance than the state-of-the-art QoS prediction models, indicating that the proposed model can be more effectively used to improve the reliable communication level of II-IoT.

An End-to-End Network Evaluation Method for Differentiated Multi-Service Bearing in VPP

Virtual power plant (VPP) plays an important role in improving the balance and regulation abilities of new power system. The safe and reliable operation is support by the VPP end-to-end communication network with differentiated multi-service bearing capability. For the requirement of unified and standard VPP end-to-end networking scheme, the VPP service communication metrics, as well as the communication network architecture of VPP aggregation and control are analyzed. Then, a multi-dimension hierarchical VPP end-to-end network evaluation index system is put forward. In addition, an end-to-end VPP network evaluation method considering differentiated time-sensitive and granular requirements of multiple services is proposed. Finally, the suitability analysis results of various end-to-end networking schemes and multiple services with differentiated time-sensitive and granular requirements are given, which plays a guiding role in establishing a unified standard VPP end-to-end networking scheme.

Delay and Energy Efficient Offloading Strategies for an IoT Integrated Water Distribution System in Smart Cities

In the fast-moving world of information and communications technologies, one significant issue in metropolitan cities is water scarcity and the need for an intelligent water distribution system for sustainable water management. An IoT-based monitoring system can improve water distribution system management and mitigate challenges in the distribution network networks such as leakage, breakage, theft, overflow, dry running of pumps and so on. However, the increase in the number of communication and sensing devices within smart cities has evoked challenges to existing communication networks due to the increase in delay and energy consumption within the network. The work presents different strategies for efficient delay and energy offloading in IoT-integrated water distribution systems in smart cities. Different IoT-enabled communication network topology diagrams are proposed, considering the different water network design parameters, land cover patterns and wireless channels for communication. From these topologies and by considering all the relevant communication parameters, the optimum communication network architecture to continuously monitor a water distribution network in a metropolitan city in India is identified. As a case study, an IoT design and analysis model is studied for a secondary metropolitan city in India. The selected study area is in Kochi, India. Based on the site-specific model and land use and land cover pattern, delay and energy modeling of the IoT-based water distribution system is discussed. Algorithms for node categorisation and edge-to-fog allocation are discussed, and numerical analyses of delay and energy models are included. An approximation of the delay and energy of the network is calculated using these models. On the basis of these study results, and state transition diagrams, the optimum placement of fog nodes linked with edge nodes and a cloud server could be carried out. Also, by considering different scenarios, up to a 40% improvement in energy efficiency can be achieved by incorporating a greater number of states in the state transition diagram. These strategies could be utilized in implementing delay and energy-efficient IoT-enabled communication networks for site-specific applications.

Integration of LiFi, BPL, and Fiber Optic Technologies in Smart Grid Backbone Networks: A Proposal for Exploiting the LiFi LED Street Lighting Networks of Power Utilities and Smart Cities

This paper presents a proposal for extending an existing terabit-class backbone network architecture to enable the use of LiFi technology by power utilities and smart cities. The proposed architecture provides a practical means of integrating three smart grid communication technologies—fiber optics, BPL networks and LiFi LED street lighting networks—across the transmission and distribution power grids of smart cities. In addition to expanding the backbone communications network architecture, the paper provides a comprehensive overview of LiFi technology and analyzes the concept of LiFi LED street lighting networks in a smart city. The analytical investigation of the operation and performance of LiFi LED street lighting networks focuses on the following aspects: (i) typical LED street lighting configurations and default configuration parameter values encountered in smart sustainable cities; (ii) the applied LiFi channel model and corresponding default model parameters; (iii) SNR computations and LiFi channel classifications for a variety of scenarios; and (iv) available LiFi LED street lighting network architectures for integrating LiFi LED street lighting networks with the backbone network. The paper also discusses the potential benefits of LiFi LED street lighting networks for power utilities, smart cities and individuals.

An endogenous intelligent architecture for wireless communication networks

AbstractThe challenges posed by the future wireless communication network, which will be a huge system with more complex structures, diverse functions, and massive communication ends, will be addressed by intelligent wireless communication technologies. These technologies are playing an increasingly important role in network architecture, computing architecture, resource allocation algorithm design, etc., thanks to the rapid development of artificial intelligence technologies, particularly the deep learning technologies, and their extensive application in various domains. In this paper, an endogenous intelligent architecture is developed to effectively clarify and understand in-depth the relationship among the factors by constructing wireless knowledge graph for the air interface transmission, the core network, as well as the network environment, and so on. Furthermore, the knowledge graph simultaneously reveals the structure and operation mechanism of the whole wireless communication networks. Cause tracing, intelligent optimization, and performance evaluation are sequentially implemented based on the knowledge graph, thus forming a complete closed-loop for endogenous intelligent wireless communication networks.

Enhancing Data Security in Autonomous Vehicle Communication Networks

In today's driving landscape, in-vehicle communication has become a cornerstone, facilitated by the proliferation of sensor-centric communication and computing devices within vehicles. These systems serve various functions such as vehicle monitoring, reducing physical wiring, and enhancing driving efficiency. However, the existing literature on cybersecurity for in-vehicle communication systems lacks dedicated solutions to mitigate in-vehicle cyber risks effectively. Current approaches primarily rely on protocol-specific security techniques, lacking a comprehensive security framework for in-vehicle communication. This paper critically examines the literature on cybersecurity for in-vehicle communication, focusing on technical architecture, methodologies, challenges, and potential solutions.
 The paper presents an in-depth analysis of in-vehicle communication network architecture, outlining key components, interfaces, and associated technologies. Protocols utilized in in-vehicle communication are classified based on their characteristics and usage types. Furthermore, security solutions for in-vehicle communication are critically reviewed, encompassing machine learning, cryptography, and port-centric techniques. A multi-layer secure framework is proposed as a protocol and use case-independent solution for in-vehicle communication security.Lastly, the paper identifies open challenges and outlines future research directions for enhancing cybersecurity in in-vehicle communication.

The Design and Optimization of an Acoustic and Ambient Sensing AIoT Platform for Agricultural Applications.

The use of technology in agriculture has been gaining significant attention recently. By employing advanced tools and automation and leveraging the latest advancements in the Internet of Things (IoT) and artificial intelligence (AI), the agricultural sector is witnessing improvements in its crop yields and overall efficiency. This paper presents the design and performance analysis of a machine learning (ML) model for agricultural applications involving acoustic sensing. This model is integrated into an efficient Artificial Intelligence of Things (AIoT) platform tailored for agriculture. The model is then used in the design of a communication network architecture and for determining the distribution of the computing load between edge devices and the cloud. The study focuses on the design, analysis, and optimization of AI deployment for reliable classification models in agricultural applications. Both the architectural level and hardware implementation are taken into consideration when designing the radio module and computing unit. Additionally, the study encompasses the design and performance analysis of the hardware used to implement the sensor node specifically developed for sound classification in agricultural applications. The novelty of this work lies in the optimization of the integrated sensor node, which combines the proposed ML model and wireless network, resulting in an agricultural-specific AIoT platform. This co-design enables significant improvements in the performance and efficiency for acoustic and ambient sensing applications.

Controllability properties for multi-agent linear systems. A geometric approach

This work addresses the controlability of a class of multi-agent linear systems that they are interconnected via communication channels. Multiagent systems have attracted much attention because they have great applicability in multiple areas, such as power grids, bioinformatics, sensor networks, vehicles, robotics and neuroscience, for example. Consequently, they have been widely studied by scientists in different fields specially in the field of control theory. Recently has taken interest to analyze the control properties as consensus controllability of multi-agent dynamical systems motivated by the fact that the architecture of communication network in engineering multi-agent systems is usually adjustable. In this paper, the control condition is analyzed under geometrical point of view. in the case of multiagent linear systems that can be described by k agents with dynamics x''_i = A_i x_i + B_i u_i, i = 1, . . . , k.

Energy efficient NOMA based beamforming and power control architecture for Future communication networks

In the current and future wireless technologies beamforming techniques are one of the key features to fit in with the higher throughput demands of users for various data exhaustive applications. Simulation of energy efficient 5G network with enabled NOMA (non orthogonal multiple access) and beamforming capabilities has been done in this paper. A partially connected hybrid beamforming architecture for multiantenna NOMA based transmitter has been proposed. A test bed of fully connected phase shifters and adjustable attenuators and multiple antennas arrays with beamforming capabilities outperform the various other sub connected models. Moreover this kind of architecture makes use of hybrid beamforming to fulfill higher capacity and low power consumption requirements of network. Simulations results are presented to demonstrate the performance of proposed architecture. Hence NOMA based trans-receivers along with hybrid beamforming technique has the potential to significantly improve the performance of the network in terms of energy efficiency.

Security optimization method of high-power charging pile inter-group communication network under trusted taboo particle swarm optimization

In order to ensure the normal operation of the communication network in the event of a small number of charging pile failures, it is necessary to establish a stable communication network between the charging pile groups. In this case, it is necessary to improve the stability and viability of the communication network between the pile groups. Based on this, this paper proposes a security optimization method for high-power inter pile communication networks under trusted tabu particle swarm optimization. Using 6LoWPAN technology to optimize the wireless communication network architecture of charging piles to reduce the probability of communication network paralysis; design a neighborhood end-to-end communication strategy, and conduct research on lightweight key management of charging piles by building a three-tier architecture for the communication environment of charging piles. The trusted taboo particle swarm optimization algorithm optimizes the security of the communication network between high-power charging piles to ensure the security of the communication network. The experimental results show that after the optimization of the proposed method, the stability and invulnerability of the communication network between the charging pile groups have been effectively improved, and the method has a high convergence speed.

GCWCN: 6G-Based Global Coverage Wireless Communication Network Architecture

At present, the world is experiencing a significant transformation from the fifth generation (5G) wireless communication network to the sixth generation (6G) wireless communication network. An important goal is to achieve seamless global coverage of wireless signals. The combination of space network, air network and ground network has been proved to be effective, but the maritime network has not been taken into account. Therefore, how to effectively achieve the global coverage of wireless networks is a challenging topic. This paper first compares the performance of 5G and 6G, and analyzes the possibility of a wireless communication network with global coverage based on 6G technology. After that, we respectively analyze the typical characteristics of space network, air network, terrestrial network and maritime network, and then lead to the key enabling technologies to combine them. Based on the typical characteristics of the above heterogeneous networks and combined with the enabling technologies, we try to propose a 6Gsupported space-air-ground-sea integrated network (SAGSIN) architecture, to achieve seamless global wireless signal coverage. In the end, we rationally analyze a series of challenges and difficulties that may be faced in implementing the architecture.

A Centralized Multi-User Anti-Composite Intelligent Interference Algorithm Based on Improved Q-Learning

This paper proposes a central anti-jamming algorithm (CAJA) based on improved Q-learning to further solve the communication challenges faced by multi-user wireless communication networks in terms of external complex malicious interference. This will also reduce the dual factors restricting wireless communication quality, the impact of inter-user interference within the network, and the effect of external malicious interference on the communication system to improve multi-user wireless communication transmission. Firstly, a central base station that coordinates and allocates channels for users within the network is set up using multi-user wireless communication network architecture to constitute a centralized wireless communication network. Secondly, the multi-user system is modeled using the single-user Markov decision process in which the central base station is the main body. Finally, an improved Q-learning algorithm is used to improve overall system transmission income using the central base station, based on the network user number sequential decision action for avoiding external malicious interference. It is designed to avoid the impact of internal network interference on transmission performance during the early stage of communication, achieving overall system transmission income improvement. Simulation results show that in comparison to the existing multi-user independent Q-learning anti-jamming algorithm and the traditional orthogonal frequency-hopping scheme, the proposed algorithm significantly improves overall system transmission performance.

Performance of Neural Computing Techniques in Communication Networks

This research investigates the use of neural computing techniques in communication networks and evaluates their performance based on error rate, delay, and throughput. The results indicate that different neural computing techniques, such as Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) and Generative Adversarial Networks (GANs) have different trade-offs in terms of their effectiveness in improving performance. The selection of technique will base on the particular requirements of the application. The research also evaluates the relative performance of different communication network architectures and identified the trade-offs and limitations associated with the application of different techniques in communication networks. The research suggests that further research is needed to explore the use of techniques, such as deep reinforcement learning; in communication networks and to investigate how the employment of techniques can be used to improve the security and robustness of communication networks.

Resource Allocation Optimization Algorithm of Power 5G Network Slice Based on NFV and SDN

To realize 5G network slicing, the virtual resource scheduling and allocation method based on NFV and SDN is designed. The scheme comprehensively considers 5G communication technology and network slice structure, and establishes the optimal mathematical model of network slice operation economy. Then the network functions and resources are virtualized by NFV and SDN, the greedy algorithm is adopted to solve the mapping problem of network slices, and the specific implementation algorithm is provided. The simulation results show that the allocation algorithm can customize the management of network slice resources, achieve flexible control and sharing of network traffic and resources, and significantly promote the construction, optimization and promotion of 5G mobile communication network architecture.

Security architecture for automotive communication networks with CAN FD

Modern vehicles have dozens of electronic modules, connected through sophisticated intra-vehicle networks, which essentially control all the vehicle functions. Recent studies have shown the vulnerability of vehicular computer systems, but the existing security models are not enough robust yet because the busload and level of cryptographic strategy are not considered enough to be implemented in the frame. This work proposes a new security model for the Controller Area Network with Flexible Data-Rate (CAN FD), based on encryption and authentication. The model divides the frame data field into two blocks. The AES-256 (Advanced Encryption Standard) symmetric key encryption is applied to the first block of the data frame, whose content is the data corresponding to the payload of the frame. The authentication of the data in the first block is executed through the implementation of the HMAC/SHA-256 function and inserted in the second block. Performance analysis has shown that the combination of 32 bytes for the first block and 32 bytes for the second one provides the shortest processing time and 33.33% fewer data compared to frame 48. Results indicated that the proposed security model has a higher encryption performance than existing methods.

Imitation Learning-Based Implicit Semantic-Aware Communication Networks: Multi-Layer Representation and Collaborative Reasoning

Semantic communication has recently attracted significant interest from both industry and academia due to its potential to transform the existing data-focused communication architecture towards a more generally intelligent and goal-oriented semantic-aware networking system. Despite its promising potential, semantic communications and semantic-aware networking are still in their infancy. Most existing works focus on transporting and delivering the explicit semantic information, e.g., labels or features of objects, that can be directly identified from the source signal. The original definition of semantics as well as recent results in cognitive neuroscience suggest that it is the implicit semantic information, in particular the hidden relations connecting different concepts and feature items that play the fundamental role in recognizing, communicating, and delivering the real semantic meanings of messages. Motivated by this observation, we propose a novel reasoning-based implicit semantic-aware communication network architecture that allows destination users to directly learn a reasoning mechanism that can automatically generate complex implicit semantic information based on a limited clue information sent by the source users. Our proposed architecture can be implemented in a multi-tier cloud/edge computing networks in which multiple tiers of cloud data center (CDC) and edge servers can collaborate and support efficient semantic encoding, decoding, and implicit semantic interpretation for multiple end-users. We introduce a new multi-layer representation of semantic information taking into consideration both the hierarchical structure of implicit semantics as well as the personalized inference preference of individual users. We model the semantic reasoning process as a reinforcement learning process and then propose an imitation-based semantic reasoning mechanism learning (iRML) solution to learning a reasoning policy that imitates the inference behavior of the source user. A federated graph convolutional network (GCN)-based collaborative reasoning solution is proposed to allow multiple edge servers to jointly construct a shared semantic interpretation model based on decentralized semantic message samples. Extensive experiments have been conducted based on real-world datasets to evaluate the performance of our proposed architecture. Numerical results confirm that iRML offers up to 25.8 dB improvement on the semantic symbol error rate, compared to the semantic-irrelevant communication solutions.

Security in Wireless Communication Networks

Over the last decade, wireless networks have experienced significant growth due to the proliferation of mobile devices and new development of radio technologies. Since the very beginning, security for wireless communication networks has always been regarded as a critical issue. In recent research frenzy on 5G and V2X communications, security plays a pivotal role as wireless Internet access serves as critical infrastructures to facilitate the digital transcations. This book timely provides a comprehensive introduction to the security in wireless communication networks, with respect to not only general concepts, but also practical principles and cases in specific wireless communication systems. This book covers a wide range starting from the general wireless communication network architecture and basic concepts of network security to the mathematical background and practical techniques, and further to the specific security issues in different wireless networks, such as WLAN, LTE, 5G, etc. Comprehensively covering the security issues, security mechanisms, design principles, and techniques in wireless communication networks. The book intends to be a self-contained and one semester textbook on wireless security for either undergraduate senior level or graduate level courses. This book can also serve as a reference for practitioners and researchers in the field to get an idea of the current and future research focus in the emerging wireless security area.

Распределенный реестр истории эксплуатации транспортного средства на основе блокчейн-платформы Hyperledger Fabric

Due to the rapid development of various transport platforms, including those using unmanned technologies, systems that provide storage of vehicle operating history throughout its lifecycle are becoming increasingly relevant. Purpose: the purpose and functionality of the developed system for storing such information are defined. The main purpose of the system is to maintain a single source of reliable and unchangeable information about the operating history of the vehicle. Such a system can increase the transparency of business processes that arise between participants in the automotive industry: manufacturers and owners of vehicles, service stations, insurance companies and other industry participants. Methods: Blockchain technology, smart contracts and various methods of transaction processing were used. Results: the system was designed based on a distributed platform, based on the criteria defined in the work, Hyperledger Fabric was chosen as the platform. Communication network and information system architecture were designed and developed based on the distributed registry technology. The paper describes the process of creating the Hyperledger Fabric network, which is supported by the member organizations of the automotive industry. A description of the basic elements of the system is presented, as well as the mechanisms that maintain and harmonize the distributed registry, transaction processing, execution of smart contracts and interaction of the connected system participants. The hardware was designed in the form of a plug-in unit, which implements the functions of collection and pre-preparation of data collected from the nodes, units, sensors of the vehicle, as well as additional sensors built into the hardware unit. The collected data are transmitted from the block to the storages, the maintenance of which is carried out by the system participants interested in such data. The fact of data transfer and data source identifier is recorded in a distributed registry in the form of a transaction, placed in the block. Practical relevance: On the basis of smart contract technology the issues of forming reports on the history of vehicle operation are considered. The system is scalable and allows the deployment of new smart contracts, which provides the ability to create new scenarios for its use. Discussion Possible variants of further development and use of the system are considered: the solution of scaling the system by local zones is proposed, and a brief overview of the approach of dynamic channel definition Hyperledger Fabric using dedicated near-field data communication is presented.

Low-Latency Autonomous Service Orchestration for the Power Communication Network

Power communication network based on optical technology can support the operation, production and scheduling of power systems. However, due to the dynamic and information uncertainty factors in the network environment, the independent service arrangement of the power communication network is faced with many challenges. To address these challenges, a software-defined network (SDN)-empowered the power communication network architecture. In this paper, we proposed a routing algorithm based on ε-greed to minimize total transmission delay of service data flow, which can support the autonomous, intelligent, and flexible orchestration for the power communication network. Simulation verify the superiority of the proposed ε-greedy algorithm in the aspect of delay and optimal path selection.