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Distributed Resource Allocation in Dispersed Computing Environment Based on UAV Track Inspection in Urban Rail Transit

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computers, Materials & Continua 2024年第7期80卷 643-660页

作者： Tong Gan Shuo Dong Shiyou Wang Jiaxin Li Division of Consulting Beijing Metro Consultancy Corporation Ltd.Beijing100037China Department of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China

With the rapid development of urban rail transit,the existing track detection has some problems such as low efficiency and insufficient detection coverage,so an intelligent and automatic track detectionmethod based onUAV is urgently needed to avoid major safety *** the same time,the geographical distribution of IoT devices results in the inefficient use of the significant computing potential held by a large number of *** a result,the Dispersed Computing(DCOMP)architecture enables collaborative computing between devices in the Internet of Everything(IoE),promotes low-latency and efficient cross-wide applications,and meets users’growing needs for computing performance and service *** paper focuses on examining the resource allocation challenge within a dispersed computing environment that utilizes UAV inspection ***,the system takes into account both resource constraints and computational constraints and transforms the optimization problem into an energy minimization problem with computational *** Markov Decision Process(MDP)model is employed to capture the connection between the dispersed computing resource allocation strategy and the system ***,a method based on Double Deep Q-Network(DDQN)is introduced to derive the optimal ***,an experience replay mechanism is implemented to tackle the issue of increasing *** experimental simulations validate the efficacy of the method across various scenarios.

关键词： UAV track inspection dispersed computing resource allocation deep reinforcement learning Markov decision process

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A Fine-Grained Flash-Memory Fragment Recognition Approach for Low-Level Data Recovery

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Chinese Journal of Electronics 2022年第4期31卷 732-740页

作者： ZHANG Li HAO Shengang ZHANG Quanxin Department of Media Engineering Zhejiang University of Media and Communication School of Computer Science Beijing Institute of Technology

Data recovery from flash memory in the mobile device can effectively reduce the loss caused by data corruption. Type recognition of data fragment is an essential prerequisite to the low-level data recovery. Previous works in this field classify data fragment based on its file type. Still, the classification efficiency is low, especially when the data fragment is a part of a composite *** propose a fine-grained approach to classifying data fragment from the low-level flash memory to improve the classification accuracy and efficiency. The proposed method redefines flash-memory-page data recognition problem based on the encoding format of the data segment, and applies a hybrid machine learning algorithm to detect the data type of the flash page. The hybrid algorithm can significantly decompose the given data space and reduce the cost of training. The experimental results show that our method achieves better classification accuracy and higher time performance than the existing methods.

关键词： Flash fragmentation recognition Fine-grained Machine learning algorithm Support vector machine Decision tree Digital forensics

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Data Secure Storage Mechanism for IIoT Based on Blockchain

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computers, Materials & Continua 2024年第3期78卷 4029-4048页

作者： Jin Wang Guoshu Huang R.Simon Sherratt Ding Huang Jia Ni School of Computer Science and Mathematics Fujian University of TechnologyFuzhou350118China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410004China School of Systems Engineering The University of ReadingReadingRG66AYUK School of Computer Nanjing University of Information Science and TechnologyNanjing210044China

With the development of Industry 4.0 and big data technology,the Industrial Internet of Things(IIoT)is hampered by inherent issues such as privacy,security,and fault tolerance,which pose certain challenges to the rapid development of *** technology has immutability,decentralization,and autonomy,which can greatly improve the inherent defects of the *** the traditional blockchain,data is stored in a Merkle *** data continues to grow,the scale of proofs used to validate it grows,threatening the efficiency,security,and reliability of blockchain-based ***,this paper first analyzes the inefficiency of the traditional blockchain structure in verifying the integrity and correctness of *** solve this problem,a new Vector Commitment(VC)structure,Partition Vector Commitment(PVC),is proposed by improving the traditional VC ***,this paper uses PVC instead of the Merkle tree to store big data generated by *** can improve the efficiency of traditional VC in the process of commitment and ***,this paper uses PVC to build a blockchain-based IIoT data security storage mechanism and carries out a comparative analysis of *** mechanism can greatly reduce communication loss and maximize the rational use of storage space,which is of great significance for maintaining the security and stability of blockchain-based IIoT.

关键词： Blockchain IIoT data storage cryptographic commitment

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A Dynamic Bayesian-Based Comprehensive Trust Evaluation Model for Dispersed Computing Environment

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China communications 2023年第2期20卷 278-288页

作者： Hongwen Hui Zhengxia Gong Jianwei An Jianzhong Qi School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Shunde Graduate School of University of Science and Technology Beijing Guangdong 528399China China Academy of Information and Communications Technology(CAICT) Beijing 100191China Department of Information Engineering North China University of TechnologyBeijing 100144China

Dispersed computing is a new resourcecentric computing *** to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its *** trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing *** this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing ***,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the *** the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding ***,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary *** experiments are introduced to verify the performance of the *** with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.

关键词： dispersed computing trust evaluation model malicious node interaction success rate detection rate

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A hybrid personality-aware recommendation system based on personality traits and types models

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12775-12788页

作者： Dhelim, Sahraoui Chen, Liming Aung, Nyothiri Zhang, Wenyin Ning, Huansheng School of Computer Science University College Dublin Dublin Ireland School of Computing Ulster University Belfast United Kingdom School of Information Science and Engineering Linyi University Linyi China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

Personality-aware recommendation systems have been proven to achieve high accuracy compared to conventional recommendation systems. In addition to that, personality-aware recommendation systems could help alleviate cold start and data sparsity problems by adding the user’s personality traits in the recommendation process. The majority of the literature works used Big-Five personality model to represent the user’s personality, this is due to the popularity of Big-Five model in the literature of psychology. However, from personality computing perspective, the choice of the most suitable personality model that satisfy the requirements of the recommendation application and the recommended content type still needs further investigation. In this paper, we study and compare four personality-aware recommendation systems based on different personality models, namely Big-Five traits model, Eysenck model and HEXACO model from the personality traits theory, and Myers–Briggs Type Indicator (MPTI) from the personality types theory. Furthermore, we propose a hybrid personality model for recommendation that takes advantage of the personality traits models, as well as the personality types models. Through extensive experiments on recommendation dataset, we prove the efficiency of the proposed model, especially in cold start settings. Our proposed hybrid personality-aware recommendation model improves the precision and recall in cold start settings by 21% and 18% respectively compared to the widely used Big-Five traits model. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Recommender systems

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Leakage Localization of Gas Pipelines Based on Modal Acoustic Emission and Cross-power Spectrum Peak Optimization

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IEEE Sensors Journal 2025年第11期25卷 19982-19992页

作者： Zhang, Wenbiao Gong, Kezheng Cui, Xiwang North China Electric Power University School of Control and Computer Engineering Beijing102206 China Beijing Information Science and Technology University School of Instrument Science and OptoElectronics Engineering Beijing100192 China

Leakage accidents in natural gas pipelines bring huge property losses and pose serious safety risks. Therefore, faster and more accurate leakage localization is of great significance. In this paper, a new method based on modal acoustic emission (MAE) and peak optimization of cross-power spectrum is proposed to enhance the performance of leakage localization. When a pipeline leakage occurs, the sensors installed on the pipelines receive the acoustic emission (AE) signals, which have various modes. Instead of extracting a single mode through complex algorithms, the proposed method directly extracts the cross-power spectrum of a specified mode by choosing the appropriate window function and window parameters to locate the leakage with velocity information from dispersion curves. Gaussian, Hamming and Blackman window functions are compared in the extraction of the cross-power spectrum of L(0,1) mode, among which the Blackman window function is found to be the most effective. The artificial fish swarm algorithm combined with the iteration criterion for peak optimization is used to obtain suitable window parameters. Finally, the localization error of the above method is less than 5.2%. In addition, the performance of the iteration criterion for peak optimization of cross-power spectrum combined with other intelligent swarm algorithms are investigated. The results show that the maximum errors of other intelligent methods are still less than 9%, demonstrating the great compatibility of the proposed method. © 2001-2012 IEEE.

关键词： Acoustic emissions

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Joint Task Offloading and Resource Allocation Strategy for Space-Air-Ground Integrated Vehicular Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1027-1043页

作者： Yuanshuo Gang Yuexia Zhang Zhihai Zhuo School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100101China

Space-Air-Ground integrated Vehicular Network(SAGVN)aims to achieve ubiquitous connectivity and provide abundant computational resources to enhance the performance and efficiency of the vehicular ***,there are still challenges to overcome,including the scheduling of multilayered computational resources and the scarcity of spectrum *** address these problems,we propose a joint Task Offloading(TO)and Resource Allocation(RA)strategy in SAGVN(namely JTRSS).This strategy establishes an SAGVN model that incorporates air and space networks to expand the options for vehicular TO,and enhances the edge-computing resources of the system by deploying edge *** minimize the system average cost,we use the JTRSS algorithm to decompose the original problem into a number of subproblems.A maximum rate matching algorithm is used to address the channel allocation and the Lagrangian multiplier method is employed for computational *** acquire the optimal TO decision,a differential fusion cuckoo search algorithm is *** simulation results demonstrate the significant superiority of the JTRSS algorithm in optimizing the system average cost.

关键词： edge computing Resource Allocation(RA) Space-Air-Ground integrated Vehicular Network(SAGVN) Task Offloading(TO)

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Nonlinear Filtering With Sample-Based Approximation Under Constrained communication:Progress, Insights and Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long Han IEEE the State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the Department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

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Improved method of dialogue model based on character and word fusion 2

Improved method of dialogue model based on character and wor...

引用

2nd International Conference on Electronic Information technology, EIT 2023

作者： Yang, Qingli Wang, Zhiliang Xiao, Ruoxiu School of Computer and Communication Engineering University of Science and Technology Beijing Shunde Innovation School Foshan China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9781510666627

ISBN: (纸本)9781510666610

An important part of the dialogue robot is the understanding of semantics and the analysis of sentences. At present, most of the models are trained based on character vector and word vector. Compared with traditional models, this method can fully consider the long and irregular language characteristics of daily chit-chat dialogues, and make full use of character and word fusion to improve the dialogue performance of the model. At the same time, the word embedding matrix trained by the pre-trained model is calculated to obtain the same dimension as the character embedding. Then, the character vector and word vector are fused, and the transformer model is used for dialogue training. The experimental results show that the proposed method can better improve the understanding ability of the dialogue model. © 2023 SPIE.

关键词： Semantics

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A Decoupling-Type Strategy for the Allen-Cahn Equation on Curved Surfaces

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Journal of Mathematical Research with Applications 2025年第1期45卷 73-83页

作者： Xiaoman XIE Qing PAN School of Computer and Communication Engineering Changsha University of Science & Technology

In this paper, we construct an efficient decoupling-type strategy for solving the Allen-Cahn equation on curved surfaces. It is based on an FEM-EIEQ(Finite Element Method and explicit-Invariant Energy Quadratization) fully discrete scheme with unconditional energy stability. Spatially the FEM is adopted, using a triangular mesh discretization strategy that can be adapted to complex regions. Temporally, the EIEQ approach is considered, which not only linearizes the nonlinear potential but also gives a new variable that we combine with the nonlocal splitting method to achieve the fully decoupled computation. The strategy can successfully transform the Allen-Cahn system into some completely independent algebraic equations and linear elliptic equations with constant coefficients, we only need to solve these simple equations at each time step. Moreover, we conducted some numerical experiments to demonstrate the effectiveness of the strategy.

关键词： FEM-EIEQ Allen-Cahn equation surface

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