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Co-Designed Communication and Computing for data Reliability in Industrial Cyber-Physical Systems with Cloud-Fog Automation

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IEEE Journal on Selected Areas in Communications 2025年

作者： Fan, Xiaoxuan Deng, Xianjun Liu, Shenghao Zhu, Chenlu Zhou, Xinlei Yi, Lingzhi Wu, Libing Park, Jong Hyuk Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Wuhan Research Institute of Posts and Telecommunications China Zhongnan University of Economics and Law School of Information Engineering China Wuhan University School of Cyber Science and Engineering China Seoul National University of Science and Technology Department of Computer Science and Engineering Korea Republic of

The Cloud-Fog Automation is a newly proposed digital industrial automation architecture aimed at accelerating the integration and collaboration of communication, computing, and control towards next-generation cyber-physical systems (CPSs). data reliability is one of the key considerations for achieving Cloud-Fog Automation. Sensor nodes serve as infrastructures for data collection within industrial CPSs and are essential for maintaining ultra-high data reliability. However, the underlying sensor nodes communicate frequently, are damage-prone and difficult to identify, which dramatically shortens the network lifetime and poses great challenges to data reliability. Motivated by this fact, this paper co-designs communication architecture, algorithms, and computing models for next-generation industrial CPSs with Cloud-Fog Automation to ensure data reliability and functional security. First, a four-layer energy-efficient communication architecture is proposed and a cluster head computing algorithm based on double deep Q-learning (CH-DDQ) is designed inside the architecture. Besides, a 2-stage hyBrid fault detection scheme (2-Brain) is proposed for underlying sensor nodes. 2-Brain first incorporates the Obstacle Triple Jump Protocol (OTP) and OTP packets to improve hard fault detection performance. Then, an unsupervised sensor reading soft fault detection model (SR-SFD) based on contrastive learning, momentum, and tensor is adopted to learn discriminative representations of sensor readings and identify soft faults. Simulations and a case study in the nuclear power industry manifest CH-DDQ improves the network lifetime by 5.4%484.3% compared to three peer methods, and OTP performs better than baselines by 33.1% on average. Additionally, SR-SFD exhibits high efficiency in sensor soft fault detection and other application scenarios. © 1983-2012 IEEE.

关键词： Cluster computing

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Detecting the Planting Holes Using Proposed Yolo-Ph Algorithm with Uva Images

SSRN

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SSRN 2025年

作者： Long, Kaiyuan Long, Jiangping Fang, Chao Li, Shibo Lin, Hui Yin, Yang Research Center of Forestry Remote Sensing & Information Engineering Central South University of Forestry and Technology Changsha410004 China College of Advanced Interdisciplinary Studies Central South University of Forestry & Technology Changsha410004 China Co. Ltd Hunan Branch Changsha410004 China Guizhou Forestry Reconnaissance & Design CO.Ltd Guiyang550001 China Hunan Key Laboratory of Forestry Remote Sensing Big Data and Security Changsha410004 China Key Laboratory of Forest Resources Management and Testing in Southern China National Forestry and Grassland Administration Changsha410004 China

The integration of UAV technology with planting hole detection offers an effective solution to address challenges such as manual counting, high labor costs, and low efficiency in large-scale planting operations. However, existing target detection algorithms face difficulties in accurately detecting planting holes based on their edge features, especially in complex scenes. To address this issue, a target detection network named YOLO-PH was designed to efficiently and rapidly detect planting holes in complex scenes. Compared to the YOLOv8 algorithm, the proposed YOLO-PH algorithm incorporates the C2f_DyGhostConv module as a replacement for both the original C2f module in the backbone network and neck network. Additionally, the ATSS label allocation method is employed to optimize sample allocation and enhance detection effectiveness. Lastly, the Siblings Detection Head is also proposed to reduce computational burden while significantly improving detection performance. Ablation experiments demonstrate notable improvements of 1.3% in mAP50 and 1.1% in mAP50:95 when using YOLO-PH compared to original algorithm. Furthermore, the proposed YOLO-PH algorithm achieves a reduction of 48.8% in FLOPs (floating point operations) and an impressive increase of 268.2 FPS (frames per second) in detection speed. Subsequent experiments on overall planting hole detection demonstrated that the proposed YOLO-PH algorithm consistently outperformed other detection algorithms across various metrics, achieving excellent precision (Accuracy = 0.91, Precision = 0.97, Recall = 0.93, F1-score = 0.95). Additionally, it exhibited low computational cost and high detection speed, laying a solid foundation for advancing precision agriculture. © 2025, The Authors. All rights reserved.

关键词： Precision agriculture

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Personalized Local Differential Privacy for Multi-dimensional Range Queries over Mobile User data

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IEEE Transactions on Mobile Computing 2025年

作者： He, Yuanyuan Wang, Meiqi Deng, Xianjun Yang, Peng Xue, Qiao Yang, Laurence T. Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210000 China

Multi-dimensional range queries performed on the mobile user data records become increasingly important and popular in the fields of e-commerce, social media, transportation logistics, etc. Meanwhile, mobile users usually have different privacy requirements for different attributes of the records. A straightforward and effective approach is to first get low-dimensional range query outcomes by using existing LDP mechanisms at different privacy levels, and then derive high-dimensional range query results at each level, and finally aggregate the results from all levels. However, it incurs low utility of the query results, since the non-fixed privacy budgets and the correlation between dimensions (attributes) detrimentally impact the utility of LDP methods, ultimately rendering them ineffective in practice. In this paper, we propose a new Personalized LDP approach for Multi-dimensional Range queries (PLDP-MR) over mobile user data, consisting of the user grouping, data perturbing, data re-perturbing, and range query results aggregating steps. First, PLDP-MR offers flexible dual grouping based on user-selected privacy levels and relevant attributes to obtain the corresponding one-dimensional and two-dimensional grids. PLDP-MR optimizes the grid granularity to minimize errors from perturbing users' attribute data with different LDP noises at non-fixed privacy levels. Furthermore, PLDP-MR carefully re-perturbs the LDP-noisy data from mobile users at lower privacy levels (i.e., having the higher utility) to achieve LDP with higher privacy levels and supplement the data volume of the corresponding groups. Thus, the data utility is effectively improved without additional privacy losses. Finally, PLDP-MR aggregates the frequencies in all the one-dimensional and two-dimensional grids related to the multi-dimensional range query at all query intervals and all privacy levels to derive the final query result with considering the correlation between attributes. The aggregations use

关键词： data privacy

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VSRQ: Quantitative Assessment Method for Safety Risk of Vehicle Intelligent Connected System

arXiv

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arXiv 2023年

作者： Zhang, Tian Guan, Wenshan Miao, Hao Huang, Xiujie Liu, Zhiquan Wang, Chaonan Guan, Quanlong Fang, Liangda Duan, Zhifei Department of Cyberspace Security College of Information Science and Technology Jinan University Guangzhou511486 China Department of Computer Science College of Information Science and Technology Jinan University Guangzhou510632 China College of Information Science and Technology Jinan University Guangdong Institution of Smart Education Jinan University Guangzhou510632 China College of Cyber Security Jinan University Guangzhou510632 China Guangdong Gene Data Processing and Analysis Engineering Research Center China Pazhou Laboratory Guangzhou510330 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Guangzhou XPeng Motors Technology Co. Ltd No.8 Songgang Road Changxing Street Cencun Tianhe District Guangzhou China

The field of intelligent connected in modern vehicles continues to expand, and the functions of vehicles become more and more complex with the development of the times. This has also led to an increasing number of vehicle vulnerabilities and many safety issues. Therefore, it is particularly important to identify high-risk vehicle intelligent connected systems, because it can inform security personnel which systems are most vulnerable to attacks, allowing them to conduct more thorough inspections and tests. In this paper, we develop a new model for vehicle risk assessment by combining I-FAHP with FCA clustering: VSRQ model. We extract important indicators related to vehicle safety, use fuzzy cluster analys (FCA) combined with fuzzy analytic hierarchy process (FAHP) to mine the vulnerable components of the vehicle intelligent connected system, and conduct priority testing on vulnerable components to reduce risks and ensure vehicle safety. We evaluate the model on OpenPilot and experimentally demonstrate the effectiveness of the VSRQ model in identifying the safety of vehicle intelligent connected systems. The experiment fully complies with ISO 26262 and ISO/SAE 21434 standards, and our model has a higher accuracy rate than other models. These results provide a promising new research direction for predicting the security risks of vehicle intelligent connected systems and provide typical application tasks for VSRQ. The experimental results show that the accuracy rate is 94.36%, and the recall rate is 73.43%, which is at least 14.63% higher than all other known indicators. Copyright © 2023, The Authors. All rights reserved.

关键词： Vehicle safety

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Secure and Privacy-preserving data-sharing Framework based on Blockchain technology for Al-Najaf/Iraq Oil Refinery

Secure and Privacy-preserving Data-sharing Framework based o...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Samir M. Umran SongFeng Lu Zaid Ameen Abduljabbar Zhi Lu Bingyan Feng Lu Zheng Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Ministry of Industry and Minerals Iraqi Cement State Company Baghdad Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China College of Education for Pure Sciences University of Basrah Technical Computer Engineering Department Al-Kunooze University College Basrah Iraq School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Huazhong Numerical Control Co. Ltd Industrial Internet Research Institute Wuhan China College of Computer Science South-Central University for Nationalities Wuhan China

The Industrial Internet of Things or Industry 4.0 efficiently enhances the manufacturing process in terms of raising productivity, system performance, cost reduction, and building large-scale systems. It enables the connection of numerous heterogeneous devices and sensors into the internet network through the utilization of revolutionary techniques that transfer the manufacturing paradigm to intelligent processes. The traditional industrial internet of things adopts centralized architectures and complex encryption algorithms that suffer from several cyber-security threats and lead to data leakage, privacy disclosure, and high computational and communicational costs. In our work, we proposed a decentralized, efficient, low-power, scalable, secure, privacy-preserving, and trusting architecture based on a private blockchain network/smart contract and interplanetary file system technology for the Al-NajafyIraq oil refinery factory. That enables autonomous working and provides a high level of security authentication and privacy preservation, P2P communication, remote access, immutability and information backtracking. Traditional blockchain technology has storage limitation issues, most recent works adopted external servers or the cloud for storage purposes. Our proposed scheme addresses the limitations of blockchain data storage by adopting an interplanetary file system (IPFS) network; provides an efficient data encryption mechanism at the perceptual layer by adopting a lightweight encryption algorithm, high-performance, and ultra-low-power consumption ARM Cortex-M microcontroller. In addition, our architecture succeeds in merging blockchain technology, IoTs, and an IPFS with the oil refinery as an industrial application area. Moreover, it provides an efficient framework that resists common cyber-security attacks and realizes cyber-security requirements represented by data availability, integrity, and confidentiality.

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Coarse-grained automatic parallelization approach for branch nested loop

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International Journal of Performability engineering 2019年第11期15卷 2871-2881页

作者： Liu, Hui Xu, Jinlong Ding, Lili College of Computer and Information Engineering Henan Normal University Xinxiang453007 China Engineering Technology Research Center for Computing Intelligence and Data Mining in Henan Province Xinxiang453007 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

GCC compiler is a retargetable compiler program that was developed to increase the efficiency of programs in the GNU system. In recent years, compiler optimization based on data dependency analysis has become an important research area of modern compilers. Existing GCC compilers can only conduct dependency analysis on perfect nested loops. In order to better explore the coarse-grained parallelism of the nested loops, we propose a dependence test method that can deal with the branch nested loops. Firstly, we identify the branch nested loop in the programs. Then, we analyze the relationship between the array subscript and the outer index variable of the branch nested loop. Finally, we calculate the distance vector of the outer loop index variable and determine whether the loop has dependence through distance vector detection. Experimental results show that our method can correctly and effectively analyze the dependence relationship of branch nested loops. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Program compilers

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Retraction notice to “Optimizing the planning of distributed generation resources and storages in the virtual power plant, considering load uncertainty” [J. Clean. Prod. 387 (2023) 135868]

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Journal of Cleaner Production 2024年 458卷

作者： Yan Zhang Fangmin Yuan Huipeng Zhai Chuang Song Roza Poursoleiman School of Mechanical and Electrical Engineering Zhengzhou University of Industrial Technology Zhengzhou Henan 451100 China National Computer Network and Information Security Management Center Henan Branch Zhengzhou 450000 China State Grid Henan Electric Power Research Institute Zhengzhou 450000 China Sun–Life Company Baku Azerbaijan

This article has been retracted: please see Elsevier Policy on Article Withdrawal ( https://***/about/policies/article-withdrawal ). Post-publication, the editor discovered suspicious changes in authorship between the original submission and the revised version of this paper. In summary, the author names Yan Zhang (new First Author and Corresponding Author), Fangmin Yuan, Huipeng Zhai and Chuang Song were added to the revised paper without explanation and without exceptional approval by the journal editor, which is contrary to the journal policy on changes to authorship. The editor reached out to the authors for an explanation, but they failed to provide a satisfactory explanation to these changes. In addition, it appears that Roza Poursoleiman was claiming an affiliation with Sun-Life Company, Baku, Azerbaijan. When questioned, the author was unable to provide convincing evidence of the existence and nature of this company. Overall, the editor feels that the findings of the manuscript cannot be relied uon and that the article needs to be retracted.

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Why Do Developers Remove Lambda Expressions in Java? 21

Why Do Developers Remove Lambda Expressions in Java?

引用

IEEE International Conference on Automated Software engineering (ASE)

作者： Mingwei Zheng Jun Yang Ming Wen Hengcheng Zhu Yepang Liu Hai Jin Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China The Hong Kong University of Science and Technology Hong Kong China Southern University of Science and Technology Shenzhen China Cluster and Grid Computing Lab School of Computer Science and Technology HUST Wuhan China

ISBN: (纸本)9781665447843

Java 8 has introduced lambda expressions, a core feature of functional programming. Since its introduction, there is an increasing trend of lambda adoptions in Java projects. Developers often adopt lambda expressions to simplify code, avoid code duplication or simulate other functional features. However, we observe that lambda expressions can also incur different types of side effects (i.e., performance issues and memory leakages) or even severe bugs, and developers also frequently remove lambda expressions in their implementations. Consequently, the advantages of utilizing lambda expressions can be significantly compromised by the collateral side effects. In this study, we present the first large-scale, quantitative and qualitative empirical study to characterize and understand inappropriate usages of lambda expressions. Particularly, we summarized seven main reasons for the removal of lambdas as well as seven common migration patterns. For instance, we observe that lambdas using customized functional interfaces are more likely to be removed by developers. Moreover, from a complementary perspective, we performed a user study over 30 developers to seek the underlying reasons why they remove lambda expressions in practice. Finally, based on our empirical results, we made suggestions on scenarios to avoid lambda usages for Java developers and also pointed out future directions for researchers.

关键词： Java Codes Computer bugs Market research Functional programming Open source software Software engineering

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Correction to: A Tree-type Multiparty Quantum Key Agreement Protocol Against Collusive Attacks

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International Journal of Theoretical Physics 2023年第5期62卷 1-1页

作者： Yang, Hao Lu, Songfeng Zhu, Jianxin Wu, Junjun Zhou, Qing Li, Tong Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center On Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China College of Management Shenzhen University Shenzhen China

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Unsupervised Domain Adaptive Person Re-Identification via Human Learning Imitation

arXiv

引用

arXiv 2021年

作者： Peng, Yang Liu, Ping Luo, Yawei Zhou, Pan Xu, Zichuan Liu, Jingen Center for Frontier AI Research Agency for Science Technology and Research Singapore Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan China College of Computer Science and Technology Zhejiang University Zhejiang Hangzhou China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Liaoning Dalian China

Unsupervised domain adaptive person re-identification has received significant attention due to its high practical value. In past years, by following the clustering and finetuning paradigm, researchers propose to utilize the teacher-student framework in their methods to decrease the domain gap between different person re-identification datasets. Inspired by recent teacher-student framework based methods, which try to mimic the human learning process either by making the student directly copy behavior from the teacher or selecting reliable learning materials, we propose to conduct further exploration to imitate the human learning process from different aspects, i.e., adaptively updating learning materials, selectively imitating teacher behaviors, and analyzing learning materials structures. The explored three components, collaborate together to constitute a new method for unsupervised domain adaptive person re-identification, which is called Human Learning Imitation framework. The experimental results on three benchmark datasets demonstrate the efficacy of our proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Students

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