Data Transmission Layer Research Articles

Integrating IoT and visual question answering in smart cities: Enhancing educational outcomes

Emerging as a paradigmatic shift in urban development, smart cities harness the potential of advanced information and communication technologies to seamlessly integrate urban functions, optimize resource allocation, and improve the effectiveness of city management. Within the domain of smart education, the imperative application of Visual Question Answering (VQA) technology encounters significant limitations at the prevailing stage, particularly the absence of a robust Internet of Things (IoT) framework and the inadequate incorporation of large pre-trained language models (LLMs) within contemporary smart education paradigms, especially in addressing zero-shot VQA scenarios, which pose considerable challenges. In response to these constraints, this paper introduces an IoT-based smart city framework that is designed to refine the functionality and efficacy of educational systems. This framework is delineated into four cardinal layers: the data collection layer, data transmission layer, data management layer, and application layer. Furthermore, we introduce the innovative TeachVQA methodology at the application layer, synergizing VQA technology with extensive pre-trained language models, thereby considerably enhancing the dissemination and assimilation of educational content. Evaluative metrics in the VQAv2 and OKVQA datasets substantiate that the TeachVQA methodology not only outperforms existing VQA approaches, but also underscores its profound potential and practical relevance in the educational sector.

Research and Simulation of OCDM Switch Layer Based on 2D WDM-Optical Code Switching Structure

Optical Communication is widely used in military and civilian backbone network communication, but due to the limitation of “electronic bottleneck”, the ability of network nodes to process information and optical layer data transmission capacity is seriously mismatched, which directly causes optical cross connectors in optical nodes. The number of ports carried has skyrocketed. In order to improve the processing speed of network nodes, this paper studies the four-layer multi-granularity switching system of optical fiber, wavelength band, wavelength, and optical code, and finally builds a complete OCDMA system through simulation software, simulates multi-user simulation, and successfully realizes The encoding and decoding process is analyzed, and the performance simulation and analysis of the core switching module of the four-layer multi-layer optical switching system-OCDM switching module are carried out, and the feasibility and superiority of the selected system are verified.

Data Fragmentation Multipath Secure Coherent Optical Communication System Based on Electrical Signal Processing

In this paper, we report a novel optical data fragmentation multipath (ODFM) scheme for coherent optical communication based on electrical signal processing in simulation. Under the control of a pseudo-random sequence (PRBS), we randomly disperse the user data and assign them to paths corresponding to different wavelengths for transmission. To reduce the hardware complexity of the system and the requirements for receiver sensitivity, we adopt binary phase shift keying (BPSK) modulation and homodyne coherent detection in the scheme. To verify the feasibility of the proposed ODFM scheme, we demonstrated an error-free transmission through 40 km fiber with 10 Gbps hopping rate and 10 Gbps data rate by the simulation tools. The proposed scheme can be widely used in the physical layer secure communication of backbone network, large-scale data transmission and physical layer encryption of free space optical (FSO) communication.

NetDDS: A Real-time Interactive Platform Based on the Publish-subscribe Mechanism

Background: With the continuous development of big data, artificial intelligence, the Internet of things, and blockchain technology, distributed interactive systems have gradually become the mainstream of computing technologies and applications with the help of real-time interaction platforms. The real-time interaction platforms provide a data communication bridge for distributed applications, not only meeting the timeliness and correctness of data interaction but also providing a unified interface for application development. It realizes the plug and play of different functional modules in the distributed system and improves development efficiency for system developers. Objective: According to the characteristics of the large scale, wide range, and complex running environment of distributed interaction systems, this paper analyzes the function and performance requirements of the distributed interactive platform and designs and implements a real-time interactive platform named NetDDS based on a publish-subscribe mechanism. Methods: Concerning the idea of a layered design, the real-time interactive platform is constructed from three aspects: distribution service layer, QoS guarantee layer, and data transmission layer. The platform provides a data synchronization function based on publish/ subscribe mechanism, a configurable QoS guarantee mechanism, and a multi-protocol data transmission mechanism based on Ethernet, ensuring the real-time correctness and reliability of data transmission. Results: Experimental results show that the interactive platform exhibits less delay in message update. Conclusion: This paper proposes a hierarchical architecture, designs and implements a real-time interaction platform based on publish/subscribe mechanism, and provides a topic- based publish/subscribe model to the application layer. The publisher and subscriber directly publish and subscribe with data as the center to meet the real-time requirements of distributed real-time applications.

Distributed Secondary Control Strategy Against Bounded FDI Attacks for Microgrid With Layered Communication Network

This paper investigates FDI attacks in distributed secondary control strategy for low inertia microgrid with a high proportion of renewable energy and power electronics. Adversaries always aim to tamper information exchange between the neighbor distributed generators (DGs) in microgrids, which results in voltage and frequency deviation leading to power breakdown. To enhance the resilience against FDI attacks of microgrid, a control network layer interconnecting with the original data transmission layer is introduced to form a layered communication network. Due to the higher openness of the layered network, the introduced control network layer also faces to potential FDI attacks. This paper proposed a distributed secondary control strategy against double-layered bounded FDI attacks rather than only attacks in the information transmission layer. The strategy can mitigate FDI attacks launched in the control network layer, and adverse influence on the data transmission layer can also be mitigated caused by FDI attacks launched in the control network layer by designing proper interconnecting matrices. In this paper, the Lyapunov theory is used to demonstrate that the strategy can make the low inertia microgrid still maintain stable against double-layered bounded FDI attacks. The effectiveness of the distributed secondary strategy against bounded FDI attacks is validated in a test microgrid consisting of 4 DGs using the Matlab/Simpower system.

Joint Optimization of Offloading and Resource Allocation for SDN-Enabled IoV

With the development of various vehicle applications, such as vehicle social networking, pattern recognition, and augmented reality, diverse and complex tasks have to be executed by the vehicle terminals. To extend the computing capability, the nearest roadside-unit (RSU) is used to offload the tasks. Nevertheless, for intensive tasks, excessive load not only leads to poor communication links but also results to ultrahigh latency and computational delay. To overcome these problems, this paper proposes a joint optimization approach on offloading and resource allocation for Internet of Vehicles (IoV). Specifically, assuming particle tasks assigned for vehicles in the system model are offloaded to RSUs and executed in parallel. Moreover, the software-defined networking (SDN) assisted routing and controlling protocol is introduced to divide the IoV system into two independent layers: data transmission layer and control layer. A joint approach optimized offloading decision, offloading ratio, and resource allocation (ODRR) is proposed to minimize system average delay, on the premise of satisfying the demand of the quality of service (QoS). By comparing with conventional offloading strategies, the proposed approach is proved to be optimal and effective for SDN-enabled IoV.

Research about the on-line system for monitoring the geological subsidence of transmission tower based on high-precision positioning of Beidou

This article proposes an innovative method to achieve Beidou high-precision positioning. Then, the online monitoring physical information system of transmission pole tower is constructed with Beidou high precision positioning and inclination measurement information as the data source. The perception layer is Beidou high-precision positioning sensor and inclination measurement sensor, the data transmission layer is the way of combining wireless private network with wired private network, and the application control layer is the data processing center, which presents the results of analyzing sensor data to the user in a visual interface. The system can send an early warning message to the user at the very early stage of the deformation of the transmission pole tower, So that the user can take measures in time.

The Comparison of Cybersecurity Datasets

Almost all industrial internet of things (IIoT) attacks happen at the data transmission layer according to a majority of the sources. In IIoT, different machine learning (ML) and deep learning (DL) techniques are used for building the intrusion detection system (IDS) and models to detect the attacks in any layer of its architecture. In this regard, minimizing the attacks could be the major objective of cybersecurity, while knowing that they cannot be fully avoided. The number of people resisting the attacks and protection system is less than those who prepare the attacks. Well-reasoned and learning-backed problems must be addressed by the cyber machine, using appropriate methods alongside quality datasets. The purpose of this paper is to describe the development of the cybersecurity datasets used to train the algorithms which are used for building IDS detection models, as well as analyzing and summarizing the different and famous internet of things (IoT) attacks. This is carried out by assessing the outlines of various studies presented in the literature and the many problems with IoT threat detection. Hybrid frameworks have shown good performance and high detection rates compared to standalone machine learning methods in a few experiments. It is the researchers’ recommendation to employ hybrid frameworks to identify IoT attacks for the foreseeable future.

Study on real-time prediction model of railway passenger flow based on big data technology

In order to solve the limitation of traditional offline forecasting application scenarios, the author uses a variety of big data open source frameworks and tools to combine with railway real-time data, and proposes a real-time prediction model of railway passenger flow. The model architecture is divided into four levels from bottom to top: data source layer, data transmission layer, prediction calculation layer and application layer. The main components of the model are data flow and prediction flow. Through message queue and ETL, the data process part realizes the synchronization of offline data and real-time data; through the big data technology frameworks such as Spark, Redis and Hive and the GBDT (Gradient Boosting Tree) algorithm, the prediction process partially realizes the real-time passenger flow of the train OD section prediction. The experimental results show that the model proposed by the author has certain practicability and accuracy both in performance and prediction accuracy.

An Extraction Method of Volleyball Spiking Trajectory and Teaching Based on Wireless Sensor Network

It is helpful to analyze volleyball spiking technology and improve spiking quality to extract volleyball spiking trajectory. This article studies the extraction method and teaching method of volleyball spiking trajectory based on a wireless sensor network. The acceleration sensor and gyroscope sensor are used to collect the spiking action state information of volleyball players. The collected information is transmitted to the PC terminal through the wireless sensor network, including physical layer, data link layer, network layer, transmission layer, and application layer, using the LEACH clustering routing protocol algorithm. In the PC terminal, the feedback filtering method is used to preprocess the received information and calculate the integral of each sensor node’s acceleration, connecting the spatial coordinates of each time to obtain the upper limb trajectory in three-dimensional space and realize the trajectory extraction of volleyball spike action. The experimental results show that the position error is less than 0.01 m and the speed error is less than 0.15 m/s. The application of this method in volleyball teaching can effectively improve the quality of volleyball teaching.

Time-Varying Error Prediction and Compensation for Movement Axis of CNC Machine Tool Based on Digital Twin

Currently, it is a challenging issue to predict the thermal-induced time-varying error for the movement axis of the computer numerical control (CNC) machine tool. Subsequently, it is a challenge to predict the machining accuracy for a certain workpiece when the machine tool and numerical control program are determined. In order to resolve this shortcoming, the time-varying error prediction and compensation for the movement axis of the CNC machine tool was studied in this article, and the advantage of digital twin in predicting the changing trend for the physical entity was applied. The framework of time-varying error prediction and compensation for the CNC machine tool's movement axis was proposed based on the digital twin concept, which includes the physical entity layer, data transmission layer, function execution layer, and application service layer. The digital twin of the movement axis, containing a time-varying error model based on heat transfer theory and visual model, was created and packaged as a ready-to-use software for predicting and compensating time-varying error. The prediction experiment of the hole-pitch time-varying error for a workpiece was carried out. It was found that the difference between prediction error and actual error is only −0.2–2.6 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m. The fluctuation range of hole-pitch error is reduced by 69.19% with the time-varying error compensation in real-time. The experimental results show that the method of time-varying error prediction and compensation based on a digital twin is an effective and feasible scheme.

An IoT-Based Life Cycle Assessment Platform of Wind Turbines

Life cycle assessment (LCA) is conducive to the change in the wind power industry management model and is beneficial to the green design of products. Nowadays, none of the LCA systems are for wind turbines and the concept of Internet of Things (IoT) in LCA is quite a new idea. In this paper, a four-layer LCA platform of wind turbines based on IoT architecture is designed and discussed. In the data transmission layer, intelligent sensing of wind turbines can be achieved and their status and location can be monitored. In the data transmission layer, the LCA platform can be effectively integrated with enterprise information systems through the object name service (ONS) and directory service (DS). In the platform layer, a model based on IMPACT 2002+ is developed, and four management modules are designed. In the application layer, different from other systems, energy payback time (EPBT) is selected as an important evaluation index for wind turbines. Compared with the existing LCA systems, the proposed system is specifically for wind turbines and can collect data in real-time, leading to improved accuracy and response time.

RIS-Aided Physical Layer Security With Full-Duplex Jamming in Underlay D2D Networks

This paper investigates the physical layer security and data transmission for the underlay device-to-device (D2D) networks, and considers a combination of the reconfigurable intelligent surface (RIS) and full-duplex (FD) jamming receiver for the robustness and security enhancements of the system. In the demonstrated spectrum sharing setup, the total power of the D2D networks is conceived to the transmitter and receiver to transmit a private message and emit the artificial noise (AN) signals. To prevent information leakage, a beamforming design is presented for a multi-antenna FD D2D receiver in order to suppress and inject the AN signals in the direction of legitimate users and eavesdropper, respectively. The statistical characterization of end-to-end RIS-assisted wireless channels is presented, and the achievable ergodic secrecy rate of the system is derived in novel approximate expressions. The numerical and simulation results confirm the accuracy and effectiveness of the proposed analytical framework. The results demonstrate an optimal selection of the D2D power allocations for different number of reflecting elements in terms of achievable ergodic secrecy rates of the system.

Design and implementation of IPv6-based face recognition in attendance management system

An IPv6-based face recognition attendance management system is proposed to improve the lack of intelligence of the existing system and improve the attendance accuracy and efficiency of attendance. This system integrates the technologies of internet of things, face recognition, IPv6, data analysis, web services, etc., and upgrades a layered software architecture, mainly including face data collection and transmission layer, face comparison information processing layer, and attendance information dissemination layer. The system has functions such as automatic face capture, face platform recognition and comparison, real-time statistics query information, etc. The application testing shows that the system can effectively collect face data of teachers and students for attendance, and has good stability of data transmission and stable human-computer operation interface. The system can provide campus service with the face as the identity mark for all teachers and students, which is of great significance for promoting the automation, intelligence and informatization of attendance.

Hierarchical model of information signals formation at the physical layer in FANET

Creation of reliable and efficient flying ad-hoc networks (FANET) requires detailed development of the model of the physical layer of data transmission, determined by the conditions of operation of the networks. The problems of well-known software simulators of communication networks are the simplified nature of the physical layer, as well as the inability to obtain specific analytical solutions in the process of simulation. The hierarchical model of formation of information signals which allows to represent various types of communication channels and the channel-forming equipment, for providing their analytical description and the further analysis is developed. The model allows to describe communication channels between UAVs and (or) ground control centers taking into account the effects of attenuation, intersymbol interference, multipath propagation of signals; schemes of terminal and intermediate network equipment with linear and nonlinear signal conversion; circuits with forward regulation, backward regulation and combined regulation; circuits with multi-channel signal generation and processing, as well as cross-links between channels. Analytical expressions of the transfer function of the generalized hierarchical model for an arbitrary number of disclosed levels of hierarchy are obtained. An example of the presentation and study of the UAV transmitter circuit on the basis of a hierarchical model of signal formation is considered.

Toward security monitoring of industrial Cyber-Physical systems via hierarchically distributed intrusion detection

Industrial Cyber-physical systems (ICPSs), integrating communication, computation and control of industrial processes are referred to as a core technology to approach the Industry 4.0. Ensuring the ICPS security is of paramount importance in smart manufacturing. Considering the characteristics of large-scale, geographically-dispersed and multi-dimensional heterogeneous, federated and life-critical natures of ICPSs, this paper investigates a hierarchically distributed intrusion detection scheme that seeks to achieve the all-round safety protection of ICPSs according to the system structure and attacking types of each ICPS layer. For physical system-relevant perceptual executive layer, potential and covert attacks are detected by the clustered sensory system state residual anomaly monitoring based on a process noise and measurement noise-adaptive Kalman filter (PNMN-AKF). PNMN-AKF can perform a joint recursive estimation of dynamic system states, time-varying process and measurement noise covariance matrices by the variational Bayes approximation framework. In cyberspace, potential cyber-attacks are detected by the anomaly monitoring of the statistical distribution of the network transmission characteristics of data transmission layer by introducing a forgetting factor-induced recursive Gaussian mixture model (FF-RGMM). In the application control layer, a regularized sparse deep belief network model is introduced to characterize the misuse behavior for detecting potential attacks. Extensive validation and comparative experiments have been conducted on a numerical simulation system and a comprehensive ICPS simulation platform by using OPNET and a commonly-used benchmark simplified Tennessee Eastman process (STEP) based on Matlab/Simulink. Experimental results demonstrate that the proposed hierarchically distributed intrusion detection method can efficiently recognize potential and covert cyber-attacks in each ICPSs link with low false alarm rate and missing detection rate, which lays a foundation for the overall security monitoring of ICPSs.

Reliable OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel

The performance of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Horizontal, shallow-water channels are characterised by extremely disadvantageous transmission properties, due to strong multipath propagation and refraction phenomena. The paper presents the results of communication tests performed during a shallow, inland-water experiment with the use of a laboratory model of a UAC system implementing the Orthogonal Frequency-Division Multiplexing (OFDM) technique. The physical layer of data transmission is partially configurable, enabling adaptation of the modulation and channel coding parameters to the specific propagation conditions. The communication tests were preceded by measurement of the UAC channel transmission properties. Based on the estimated transmission parameters, four configurations of OFDM modulation parameters were selected, and for each of them, communication tests were performed with the use of two Error-Correction Coding (ECC) techniques. In each case, the minimum coding rate was determined for which reliable data transmission with a Bit Error Rate (BER) of less than 10 − 4 is possible.

For intelligent debugging management of offshore oil engineering with big data

With the development of science and technology, in the field of oilfield commissioning, the requirements for process management are more and more standardized and scientific, and the requirements for decentralized equipment status detection and maintenance are also higher and higher. It is the hope of any manager to eliminate hidden dangers and prevent them in a timely manner. This paper introduces an intelligent debugging model based on big data. Based on the big data mechanism, the model is divided into different functions according to different functions and requirements. It can ensure the authenticity of debugging data, coordinate all big data work through the big data communication mechanism, and conduct scientific management of debugging data. The model is divided into three levels: data acquisition layer, data transmission layer and control management layer. The offshore oil intelligent debugging platform software based on big data technology is built. A new intelligent debugging method for offshore oil based on big data is presented to study the warning information, fault location and equipment health status of intelligent debugging. Development for Marine oil intelligent debugging applications, for business people to provide intelligent Marine oil intelligent debugging method, provide data support for management decision-making, implementation of the lean management data in the field of intelligent debugging, improving the capacity of intelligent debugging data analysis and mining, effective use of the existing intelligent debugging automation system and other related data in the system, solved the “huge amounts of data, information, the lack of a” awkward situation, improve intelligence debugging application function, meet the demand of intelligent debugging of each department, improve the efficiency of debugging and running reliability and intelligent management.

Improving Physical Layer Security of Cellular Networks Using Full-Duplex Jamming Relay-Aided D2D Communications

This paper investigates the physical layer security and data transmission in cellular networks with inband underlay Device-to-Device (D2D) communications, where there is no direct link between D2D users. We propose to apply full-duplex (FD) transmission and dual antenna selection at the D2D relay node. The relay node can simultaneously act as a friendly jammer to improve the secrecy performance of the cellular network while enhancing the D2D communication data transmission. This is an appealing and practical scheme where spectrum sharing is beneficial for the D2D and cellular networks in terms of reliability enhancement and security provisioning, respectively. The practical scenario, where the eavesdropper is passive, is considered. The eavesdropper uses either selection combining or maximal ratio combining to combine the wiretapped signals of the cellular network. The secrecy performance of the cellular network is analyzed, and closed-form expressions for the secrecy outage probability and the probability of non-zero secrecy capacity are derived. We show that increasing the number of FD jamming antennas enhances the secrecy performance of the cellular network. A closed-form expression of the D2D outage probability is also provided. Simulation and numerical results are provided to verify the efficiency of the proposed scheme and to validate the accuracy of the derived expressions.

Design of real-time monitoring and intelligent management cloud platform for entire process of construction waste

In order to achieve real-time detection and intelligent control of generation links, transportation processing links, resource utilization and application of recycled products about construction waste, the real-time monitoring and intelligent control cloud platform is studied. This platform can dock urban external construction departments, urban management departments and other external e-government systems to achieve the aims of entire process detection and intelligent resource utilization. This paper studies the design and implementation of real-time monitoring and intelligent control cloud platform for construction waste. This platform is divided into three parts: the data acquisition layer, the data transmission layer, the big data processing layer and application service layer. The article focuses on the functions and technical implementation of each layer: data access design including big data monitoring technology in the whole process of construction waste control, storage design of cloud computing collaborative service technology in the whole process of construction waste control, real-time 3D visualization software and hardware support based on space-time cloud platform.