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Stochastic Nonlinear Analysis of internet of things Network Performance and Security

International Journal of Advanced Computer Science and applications 2025年第4期16卷 460-470页

作者： Li, Junzhou Sun, Feixian Information Management Center Kaifeng University Kaifeng China School of Electronics and Internet of Things Henan Polytechnic Zhengzhou China Zhengzhou Key Laboratory of Electronic Intelligent Sensor Application Technology Zhengzhou China

Aiming at the problem of poor effect of traditional internet of things network performance and security analysis methods, the research uses support vector machine for internet of things network security situation assessment. It also introduces the grey wolf optimization algorithm improved by genetic algorithm to optimize it, and designs a stochastic nonlinear integration of internet of things network performance algorithm. The results revealed that the mean absolute error, root mean square error, and mean absolute percentage error of the integrated algorithm were 0.0064, 0.041, and 0.0013, respectively, in the performance test. It was significantly lower than that of the other four algorithms, which proved that its prediction accuracy was higher. The recall of the integrated algorithm was 93.7%, and the F1 value was 0.94, which was significantly higher than the other comparative algorithms, proving its better comprehensive performance. In the analysis of practical application effect, when access control was performed by the integrated algorithm, the predicted curve basically overlapped with the actual curve, which proved its better fitting performance. The communication overhead of the integrated algorithm was 81.3 KB, which was significantly lower than the other two calculations. The average communication time of the integrated algorithm was 3.59 s, which was lower than the other two algorithms, proving that it can effectively reduce the communication cost and delay. The integrated algorithm can effectively improve the performance of internet of things network security situation assessment, which provides reliable technical support for the security protection of internet of things network and has important practical application value. © (2025), (Science and Information Organization). All rights reserved.

关键词： Genetic algorithms

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Study on moisture absorption characteristics of glass fibrereinforced epoxy resin material for composite insulators based on the 3D-Fick model

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High Voltage 2024年第4期9卷 888-901页

作者： Yuming Zhang Yunpeng Liu Sizu Hou Jianghai Geng Ping Wang Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense North China Electric Power UniversityBaodingChina Hebei Key Laboratory of Power Internet of Things Technology BaodingChina

Long-term exposure to moisture leads to a gradual deterioration of performance and reduced service life of glass fibre-reinforced epoxy resin(GFRP)material in composite ***,it is necessary to analyse the moisture absorption characteristics of GFRP material and the evolution of damage to their internal interface *** absorption tests on GFRP rod material used in composite insulators to obtain their three-dimensional diffusion coefficients are *** force microscopy was then employed to obtain the composite material system's fibre/matrix interfacial phase ***,a finite element model incorporating representative volume elements with interfacial phases and a mesoscale transient moisture absorption finite element model for the composite material was ***,the moisture absorption characteristics of GFRP material and the evolution of damage to the interfacial phase under thermal-humidity cycling conditions were *** results showed that the diffusion coefficient along the fibre direction in GFRP material was higher than that in the perpendicular *** moisture diffusion finite element model,incorporating an anisotropic interfacial phase,fitted the anisotropic diffusion coefficients of GFRP material more *** moisture invaded the GFRP material,the mismatch stresses continuously increased during the moisture ***,the non-uniform arrangement of fibres resulted in uneven distribution of moistureinduced stresses inside the material,leading to higher mismatch stresses in areas with dense fibre arrangements in the *** high and low humidity cycles led to the development of micro-cracks,micro-porosity,and interface debonding along the fibre direction at the GFRP material interfaces,thereby affecting the anisotropic moisture absorption characteristics of the *** findings of this study provide valuable insights into the mechanisms underlying the

关键词： composite fibre moisture

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Enhanced VR Experience with Edge Computing: The Impact of Decoding Latency

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IEEE Transactions on Mobile Computing 2025年第7期24卷 6275-6292页

作者： Huang, Liang Li, Yuqi Liang, Hongyuan Chi, Kaikai Wu, Yuan Zhejiang University of Technology School of Computer Science and Technology China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Macau China

Virtual reality (VR) applications have revolutionized digital interaction by providing immersive experiences.360° VR video streaming has experienced significant growth and popularity as a pivotal VR application. However, the combination of limited network bandwidth and the demand for high-quality videos frequently hinders the achievement of a satisfactory quality of experience (QoE). Although prior methods have enhanced QoE, the effects of decoding latency have been poorly studied. It is technically challenging to design a quality adaptation algorithm that can balance the pursuit of high-quality videos and the limitation of limited bandwidth resources. To address this challenge, we propose an edge-end architecture for 360° VR video streaming and aim to enhance overall QoE by solving a performance optimization problem. Specifically, our experiments on commercial mobile devices in real-world situations reveal that decoding latency significantly influences QoE. First, decoding latency plays a major role in contributing to end-to-end latency, which exceeds the transmission latency. Second, decoding latency can differ considerably between devices with varying computational capabilities. Building on this insight, we propose a novel latency-aware quality adaptation (LAQA) algorithm. LAQA lies in developing a solution that can allocate video quality in real-time and enhance overall QoE. LAQA involves not only the quality of the received content, the transmission latency and the quality variance, but also the decoding latency and the fairness of the user quality. Subsequently, we formulate a combinatorial optimization problem to maximize overall QoE. Through extensive validation with experimental data from real-world situations, LAQA offers a promising approach to enhance QoE and ensure fairness performance in different devices. In particular, LAQA achieves 16.77% and 10.66% enhancement over the state-of-the-art combinatorial optimization and reinforcement learning algorithm

关键词： Bandwidth

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Stochastic Unit Commitment with High-Penetration Offshore Wind Power Generation in Typhoon Scenarios

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 535-546页

作者： Yanqi Liu Dundun Liu Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China University of Macao Zhuhai UM Science and Technology Research Institute ZhuhaiChina

To tackle the energy crisis and climate change,wind farms are being heavily invested in across the *** China's coastal areas,there are abundant wind resources and numerous offshore wind farms are being *** secure operation of these wind farms may suffer from typhoons,and researchers have studied power system operation and resilience enhancement in typhoon ***,the intricate movement of a typhoon makes it challenging to evaluate its spatial-temporal *** published papers only consider predefined typhoon trajectories neglecting *** address this challenge,this study proposes a stochastic unit commitment model that incorporates high-penetration offshore wind power generation in typhoon *** adopts a data-driven method to describe the uncertainties of typhoon trajectories and considers the realistic anti-typhoon mode in offshore wind farms.A two-stage stochastic unit commitment model is designed to enhance power system resilience in typhoon *** formulate the model into a mixed-integer linear programming problem and then solve it based on the computationally-efficient progressive hedging algorithm(PHA).Finally,numerical experiments validate the effectiveness of the proposed method.

关键词： Unit commitment two-stage stochastic programming offshore wind farm typhoon

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Debris flow runout behaviors considering the influences of densely populated buildings

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Journal of Mountain Science 2024年第8期21卷 2696-2712页

作者： ZHANG Shuai FANG Zhe DAI Cong WANG Shuairong PENG Jingyu ZHOU Yiling SHEN Ping MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering Zhejiang UniversityHangzhou 310058China State Key Laboratory of Internet of Things for Smart City and Department of Ocean Science and Technology University of MacaoMacao SAR 999078China

Debris flows pose serious risks to communities in mountainous areas,often resulting in large losses of human life and *** impeding presence of urban buildings often affects the runout behavior and deposition of debris *** the impact of different building densities and sizes on debris flow dynamics has yet to be quantified to guide urban planning in debris flow risk *** study focused on a debris flow that occurred in Zhouqu County,Gansu Province,China on August 7th,2010,which was catastrophic and destroyed many *** FLO-2D software was used to simulate this debris flow in two scenarios,*** presence and the absence of buildings,to obtain debris-flow intensity *** developed model was then used to further analyze the influence of large buildings and narrow channels within the urban *** simulation results show that considering the presence of buildings in the simulation is essential for accurate assessment of debris flow intensity and deposition *** layout of buildings in the upstream urban area,such as large buildings or parallel buildings which form narrow channels,can affect the flow velocity and depth of debris flow heading towards downstream *** mitigate damage to downstream buildings,the relative spacing(d/a)between upstream and downstream buildings should not exceed a value of two and should ideally be even *** findings provide valuable insights for improving the resistance of mountainous cities to urban debris flows.

关键词： Debris flow Risk Building blockage effect Zhouqu Urban layout

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PLC for In-Vehicle Network: A DRL-Based Algorithm of Diversity Combination of OFDM Subcarriers

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Chinese Journal of Electronics 2023年第6期32卷 1245-1257页

作者： CHEN Zhixiong ZHANG Zhikun CAO Tianshu ZHOU Zhenyu School of Electrical and Electronic Engineering North China Electric Power University Hebei Key Laboratory of Power Internet of Things Technology

For low latency communication service of vehicles, it is critical to improve the delay performance of power line communication(PLC) for in-vehicle network,which can decrease the weight and cost of the vehicle. In order to minimize the total time slots used in a transmission task, an orthogonal frequency-division multiplexing(OFDM) subcarrier diversity combination algorithm of PLC based on the deep reinforcement learning(DRL) is proposed herein. The short packet communication theory is used to develop an optimal combination model with constraints on short packet reliability, transmitting power and the amount of data. The state, action, and reward function of double deep Q-learning network(DDQN) are defined, and diversity combination for OFDM subcarriers is performed using DDQN. An adaptive power allocation algorithm based on the thresholds of error rate and the data amount is used. Simulation results show that the proposed algorithm can effectively improve the delay performance of PLC under the constraints of power and data amount.

关键词： Q-learning OFDM Simulation Power line communications Reliability theory Delays Resource management

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Privacy-preserving IoT system based on blockchain and proxy re-encryption

Privacy-preserving IoT system based on blockchain and proxy ...

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2023 International Conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2023

作者： Cai, Linqing Yang, Yanhua School of Information Science and Engineering Yunnan University Yunnan Province 650500 China University Key Laboratory of Internet of Things Technology and Application Yunnan Province 650500 China

ISBN: (纸本)9781510677685

internet of things (IoT) technology is widely used across various domains, generating a substantial volume of data from IoT devices. These data often contains sensitive information pertaining to individuals and organizations. As a result, ensuring the privacy and security of IoT data has become a top priority. Many users prefer to connect their IoT devices to semi-trusted IoT cloud platforms. However, existing IoT cloud platforms often fail to adequately safeguard data privacy. Furthermore, most IoT data privacy protection schemes tend to overlook privacy and security concerns within this context. To address these challenges, this paper introduces a solution for IoT data privacy protection. This solution builds upon the existing architecture of IoT cloud platforms and incorporates blockchain and proxy re-encryption technology to enhance the privacy and security of IoT data. This approach achieves decentralized access control through blockchain technology and employs proxy re-encryption for end-to-end encrypted data transmission. We have developed a prototype system for this solution, including IoT client and server applications, Distributed applications (DApps), and blockchain smart contracts. Experimental results demonstrate that this solution delivers excellent encryption and decryption performance, thereby ensuring data privacy and security. In comparison to existing solutions employing Attribute-Based Encryption (ABE), our approach offers enhanced feasibility and effectiveness. It presents an improved path for existing IoT cloud platforms to securely and reliably handle sensitive data, with promising applications across various domains. © 2024 SPIE.

关键词： Smart contract

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Improved YOLOv5 algorithm for small object detection in UAV aerial imagery 4

Improved YOLOv5 algorithm for small object detection in UAV ...

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4th International Conference on Advanced Algorithms and Neural Networks, AANN 2024

作者： Cai, Linqing Yang, Yanhua School of Information Science & Engineering Yunnan University Yunnan Province 650500 China University Key Laboratory of Internet of Things Technology and Application Yunnan Province 650500 China

ISBN: (纸本)9781510686106

Due to complex backgrounds, varying object scales, and many small objects in Unmanned Aerial Vehicle (UAV) imagery, existing algorithms often have low detection accuracy, especially for small objects. To tackle these issues, we propose an improved YOLOv5-based algorithm. A Backbone Feature Weighted Fusion (BFWF) module is introduced to extract and fuse multi-scale features from the backbone. These extracted features are fused with the original neck output through cross-neck connections, enhancing fine-grained features. The neck structure is adjusted to improve the diversity and weighting of shallow fine-grained features. An Adaptive Spatial Feature Fusion (ASFF) module dynamically fuses features at different levels in the Path Aggregation Network (PANet), improving small object detection accuracy. By replacing the original loss function with the Efficient Intersection over Union (EIoU) loss function, we achieve more precise learning of small object dimensions across multi-scale scenarios. Experiments on the VisDrone2021 dataset show that the improved algorithm increases mAP50 by 3.7%, mAP75 by 2.5%, and mAP50:95 by 2.4% compared to the original YOLOv5 algorithm. This significantly enhances detection performance, making it more suitable for UAV imagery. © 2024 SPIE.

关键词： Aerial photography

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Two-Stage Client Selection Scheme for Blockchain-Enabled Federated Learning in IoT

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Computers, Materials & Continua 2024年第11期81卷 2317-2336页

作者： Xiaojun Jin Chao Ma Song Luo Pengyi Zeng Yifei Wei Beijing Key Laboratory of Work Safety Intelligent Monitoring School of Electronic EngineeringBeijing University of Posts and TelecommunicationsBeijing100876China Institute of Industrial Internet and Internet of Things China Academy of Information and Communications TechnologyBeijing100191China

Federated learning enables data owners in the internet of things(IoT)to collaborate in training models without sharing private data,creating new business opportunities for building a data ***,in practical operation,there are still some problems with federated learning *** has the characteristics of decentralization,distribution,and *** blockchain-enabled federated learning further improve the security and performance of model training,while also expanding the application scope of federated *** has natural financial attributes that help establish a federated learning data ***,the data of federated learning tasks may be distributed across a large number of resource-constrained IoT devices,which have different computing,communication,and storage resources,and the data quality of each device may also ***,how to effectively select the clients with the data required for federated learning task is a research *** this paper,a two-stage client selection scheme for blockchain-enabled federated learning is proposed,which first selects clients that satisfy federated learning task through attribute-based encryption,protecting the attribute privacy of *** blockchain nodes select some clients for local model aggregation by proximal policy optimization *** show that the model performance of our two-stage client selection scheme is higher than that of other client selection algorithms when some clients are offline and the data quality is poor.

关键词： Blockchain federated learning attribute-based encryption client selection proximal policy optimization

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H∞ containment control for multi-unmanned aerial vehicle systems: A self-triggered control scheme

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Journal of the Franklin Institute 2024年第2期361卷 572-582页

作者： Wang, Shiyi Cao, Zhiru Peng, Chen Zhu, Kaiqun Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai China The State Key Laboratory of Internet of Things for Smart City University of Macau Macau999078 China

This paper is concerned with the containment control problem for multi-unmanned aerial vehicle (multi-UAV) systems with data transmission among agents during a limited-bandwidth network. A good deal of data transmitted during a limited-bandwidth network may result in data collision, which brings negative effects on controller design and containment tracking implementation. To reduce the network load during data transmission, a consensus condition and a triggering subsidiary condition are first proposed to realize the containment tracking with H∞ performance by using the triggered states. Then a self-triggered scheme is established under a multi-agent framework, in which the next triggering instant is calculated beforehand by using the past states. Combined with the self-triggered scheme, a containment controller is obtained via solving the derived consensus condition, which ensures that follower UAVs are driven into a convex set surrounded by leader UAVs. Finally, the validity of the self-triggered containment control method is proved through a simulation experience. © 2023 The Franklin Institute

关键词： Unmanned aerial vehicles (UAV)

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