Article
Automation & Control Systems
Yayu Peng, Wei Qiao, Liyan Qu
Summary: This article proposes a compressive sensing-based missing-data-tolerant fault detection method for remote condition monitoring of wind turbines. It increases the sparsity of the collected signals, samples them using a compressive-sensing-based algorithm, and reconstructs the signals at the receiving end to detect faults in wind turbines.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Information Systems
Muhammad Bukhsh, Saima Abdullah, Abdul Rahman, Mamoona Naveed Asghar, Humaira Arshad, Abdulatif Alabdulatif
Summary: The Internet of Things (IoT) is a highly influential and promising technology that allows wireless connections between different objects and items. Clusters in the IoT system are controlled by a central authority, and the concept of backup data helps increase the lifespan of IoT subgroups for smooth transmission of packets and improved availability. The proposed Energy Efficient Message Scheduling algorithm enhances the fault-tolerant and available schemes for IoT systems while prolonging the battery-powered network lifetime, showing effectiveness and efficiency.
Article
Computer Science, Information Systems
Ankur Choudhary, Santosh Kumar, Krishna Pal Sharma
Summary: Wireless sensor networks are self-organizing systems that can operate in various environments. However, data delivery in these networks is often faulty and unpredictable. This work proposes a scheme for detecting and classifying faults in clustered wireless sensor networks, which can improve fault detection accuracy and data quality.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2022)
Article
Automation & Control Systems
Hyun Jun Jung, Amin Toghi Eshghi, Soobum Lee
Summary: This article introduces a new self-powered wireless failure detection method using piezoelectric energy harvesters with different signal transmission rates. By utilizing multifunctional piezoelectric materials and a power management circuit, the system successfully monitored screw joint failure in a vibrating plate.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2021)
Article
Computer Science, Hardware & Architecture
Romany F. Mansour, Suliman A. Alsuhibany, Sayed Abdel-Khalek, Randa Alharbi, Thavavel Vaiyapuri, Ahmed J. Obaid, Deepak Gupta
Summary: Wireless Sensor Networks (WSN) is a hot research topic that requires improving network survivability. The proposed EAFTC-RIS technique enhances network survivability by optimizing the selection of cluster heads and optimal routes, as well as employing a fault tolerant mechanism.
Article
Engineering, Electrical & Electronic
Hossein Darvishi, Domenico Ciuonzo, Eivind Roson Eide, Pierluigi Salvo Rossi
Summary: This article introduces a machine-learning-based sensor validation architecture that uses neural network estimators and a classifier to detect and isolate faulty sensors for reliable digital twins. Results show that the proposed architecture performs well under different real-world datasets and synthetically-generated faults.
IEEE SENSORS JOURNAL
(2021)
Article
Chemistry, Analytical
Dominik Widhalm, Karl M. Goeschka, Wolfgang Kastner
Summary: This study introduces a novel sensor node platform with low-power components and self-diagnostic measures, aiming to enhance the reliability and data quality of wireless sensor networks. It shows significant improvements in detecting node faults and distinguishing between proper events and fault-induced data distortion, with negligible impact on energy efficiency and hardware costs.
Article
Computer Science, Information Systems
Nabajyoti Mazumdar, Amitava Nag, Sukumar Nandi
Summary: This paper focuses on developing an energy-efficient data dissemination protocol for sensor to ES communication in Wireless Sensor Networks, aiming to preserve network coverage and support dynamic changes in network topology. By considering only local information of sensor nodes, the proposed protocol shows greater efficiency in various parameters compared to many state-of-the-art protocols.
Article
Computer Science, Information Systems
Huynh A. D. Nguyen, Quang P. Ha
Summary: This paper presents a low-cost wireless sensor network enabled by the Internet of Things, which improves reliability for monitoring air quality in suburban areas. The proposed network achieves high availability with regards to energy consumption and data assurance, with a survival probability of over 80% during a minimum period of 72-hour operation. The study also shows the high correlations between the developed system and benchmark monitoring stations.
Article
Computer Science, Information Systems
Frederico Cerveira, Raul Barbosa, Henrique Madeira, Filipe Araujo
Summary: Virtualized servers are widely used in cloud computing environments to host online applications and provide elastic computing resources. However, the presence of soft errors in large-scale servers can lead to various failure modes, with hang failures being the most common. A recovery mechanism using online testing is developed to address these hang failures and ensure server uptime.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Automation & Control Systems
Kazim Selim Engin, Volkan Isler
Summary: This article discusses the problem of establishing fault-tolerant mobile networks with dispersed robots in large areas, presenting an algorithm that efficiently relocates robots to form a connected network. Through large-scale simulations, the algorithm's performance is demonstrated and improved for randomly chosen starting locations of robots.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2021)
Article
Computer Science, Hardware & Architecture
Mingru Dong, Haibin Li, Yongtao Hu, Haocai Huang
Summary: With the development of Marine Internet of Things, the energy-efficient and fault-tolerant UASN topology is generated in this paper to address the limited energy and potential node failures in UASN. By optimizing the transmission power of each node and considering node load, the node lifetime and the preferential growth mechanism are improved. Simulation experiments show that the generated topology outperforms other existing topologies in terms of fault tolerance and energy efficiency.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Automation & Control Systems
Gagandeep Kaur, Prasenjit Chanak, Mahua Bhattacharya
Summary: The demand for Industrial Internet of Things (IIoT) technology has seen a significant increase in various industries such as agriculture, mining, factories, and healthcare. Industrial wireless sensor networks (IWSNs) act as the backbone of IIoT systems by connecting heterogeneous sensors. However, IWSNs are prone to faults due to harsh environments and the presence of obstacles. This article proposes an optimal fault diagnostic point selection mechanism that reduces fault detection latency and energy consumption. The use of intelligent mobile fault detectors improves fault detection accuracy and effectively avoids obstacles. Extensive simulations and experiments demonstrate the effectiveness of the proposed scheme in terms of various performance metrics.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Hardware & Architecture
Atakan Aral, Vincenzo De Maio, Ivona Brandic
Summary: Wireless sensor networks are important for monitoring applications, but limitations in energy, processing power, and network bandwidth hinder real-time requirements in IoT applications. Deploying edge nodes in urban areas requires consideration of reliability and environmental sustainability. This paper proposes the ARES algorithm, which uses multi-objective optimization and a dynamic Bayesian network model to achieve sustainable and reliable edge node deployment in urban areas.
IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING
(2022)
Article
Computer Science, Information Systems
Zaid Yemeni, Haibin Wang, Waleed M. Ismael, Ammar Hawbani, Zhengming Chen
Summary: This article proposes a centralized approach for detecting and recovering faulty data in WSNs. It operates in two phases to clean the data and identify different types of faults. Experimental results demonstrate the effectiveness of the proposed method compared to existing techniques for the same application.
IEEE SYSTEMS JOURNAL
(2022)
Article
Automation & Control Systems
Yang Xu, Md Zakirul Alam Bhuiyan, Tian Wang, Xiaokang Zhou, Amit Kumar Singh
Summary: In this article, we propose a framework called C-fDRL to protect the context-aware privacy of task offloading using context-aware federated deep reinforcement learning. The framework operates in three stages (CloudAI, EdgeAI, and DeviceAI) of the overall system, decoupling data from tasks through a context-aware data management approach for local and edge computation, leading to improved data privacy protection.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Liang Wang, Zhiwen Yu, Kaishun Wu, Dingqi Yang, En Wang, Tian Wang, Yihan Mei, Bin Guo
Summary: Mobile Crowdsensing (MCS) is an appealing paradigm for collaboratively collecting data from surrounding environments by assigning outsourced sensing tasks to volunteer workers. However, unpredictable disruptions during task implementation often result in task execution failure and impair the benefit of MCS systems. In this work, we propose a robust task assignment scheme that proactively creates assignments offline, aiming to strengthen the robustness of the scheme and minimize workers' traveling detour cost. By leveraging workers' spatiotemporal mobility, we construct an assignment graph and use an evolutionary multi-tasking optimization algorithm (EMTRA) to achieve adequate Pareto-optimal schemes. Comprehensive experiments on real-world datasets validate the effectiveness and applicability of our approach.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Jing Bai, Zhiwen Zeng, Tian Wang, Shaobo Zhang, Neal N. Xiong, Anfeng Liu
Summary: In this article, a trust-based active notice task offloading (TANTO) scheme is proposed to provide trust and low-delay task offloading for resource-limited IoT devices in areas with no available communication infrastructure. The main innovations of TANTO include a novel task offloading mechanism, a trust calculation and reasoning method, and an online UAV trajectory optimization algorithm. Experimental results show that TANTO outperforms previous studies in terms of task completion rate, tasks' average completion time, and UAV's flight cost.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Theory & Methods
Jiang Xiao, Huichuwu Li, Minrui Wu, Hai Jin, M. Jamal Deen, Jiannong Cao
Summary: This article introduces the latest research progress in wireless device-free human sensing (WDHS) technology, classifying the systems into different categories and discussing various sensing task types and motion granularity. The article also proposes a new research framework to summarize WDHS systems, and presents future research directions in terms of data collection, sensing methodology, performance evaluation, and application scenarios.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Lei Yang, Jiaming Huang, Wanyu Lin, Jiannong Cao
Summary: Personalized federated learning (PFL) provides personalized models that fit the local data distribution of each client. We propose a Group-based Federated Meta-Learning framework (G-FML) that adaptively divides clients into groups based on data distribution similarity to achieve personalized models. Experimental results show that our framework improves model accuracy by up to 13.15% compared to state-of-the-art federated meta-learning.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2023)
Article
Computer Science, Theory & Methods
Juncen Zhu, Jiannong Cao, Divya Saxena, Shan Jiang, Houda Ferradi
Summary: Federated learning is a privacy-preserving machine learning technique that trains models across multiple devices without exchanging local data samples. Existing centralized solutions have disadvantages, and blockchain has been identified as a potential solution. This work comprehensively surveys challenges, solutions, and future directions for blockchain-empowered federated learning.
ACM COMPUTING SURVEYS
(2023)
Article
Engineering, Electrical & Electronic
Rongling Yu, Ping He, Heng Li, Jiannong Cao, Feiqi Deng
Summary: This article investigates the consensus problem of linear multi-agent systems (MASs) with unknown external disturbances under intermittent communication. Firstly, the distributed extended observer is utilized to observe the relative output information and unknown disturbance. Then, a distributed active disturbance rejection intermittent consensus protocol is proposed using the observer information. Finally, a simulation example is provided to demonstrate the effectiveness of the consensus protocol.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Editorial Material
Automation & Control Systems
Md Zakirul Alam Bhuiyan, Sy-Yen Kuo, Guojun Wang
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Civil
Zhaoyang Wang, Song Wang, Md Zakirul Alam Bhuiyan, Jiping Xu, Yanzhu Hu
Summary: This paper proposes a federated cryptosystem localization based on optimized constraints to protect the security of a cooperative location-sensing system. By defining a penalty function and utilizing the Paillier cryptosystem for encryption, privacy preservation against attacks is achieved.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Zengcheng Sun, Ping He, Heng Li, Jiannong Cao, Feiqi Deng
Summary: The group consensus of second-order sample multi-agent systems is investigated using a distributed event-triggered mechanism. A consensus protocol is proposed, which is updated only when the event-triggered condition is met and the update only depends on the data collected at the moment of triggering. The sufficient condition for group consensus is obtained, and a differential equation is constructed to avoid the Zeno phenomenon and obtain a minimum positive and lower bound for any two trigger time intervals. The effectiveness is verified through a simulation example.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Wei Li, Jinlin Chen, Jiannong Cao, Chao Ma, Jia Wang, Xiaohui Cui, Ping Chen
Summary: In this article, a new augmentation model called EID-GANs is proposed to address the extremely imbalanced data augmentation problem. The model utilizes a new penalty function to guide the generator in learning the features of outliers and incorporates outlier detectors for evaluating the availability of generated instances. Experimental results demonstrate that EID-GAN outperforms existing augmentation models on different imbalanced datasets.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Civil
Hanqing Wu, Shan Jiang, Jiannong Cao
Summary: Supply chain traceability requires transparency, authenticity, and high efficiency in product tracking. Blockchain has been widely adopted for transparency and authenticity, but the efficiency issue has been overlooked.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Wei Liang, Yang Yang, Ce Yang, Yonghua Hu, Songyou Xie, Kuan-Ching Li, Jiannong Cao
Summary: The article introduces the personal data privacy protection scheme PDPChain based on consortium blockchain, which uses an improved Paillier homomorphic encryption mechanism and CP-ABE to achieve fine-grained access control, ensuring user privacy and security. Experimental results validate the effectiveness of the scheme in reducing encryption and decryption time.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Computer Science, Artificial Intelligence
Yu Yang, Hongzhi Yin, Jiannong Cao, Tong Chen, Quoc Viet Hung Nguyen, Xiaofang Zhou, Lei Chen
Summary: Dynamic graphs are graphs whose structure changes over time. Existing approaches only consider dynamic graphs as a sequence of changes in vertex connections, ignoring the asynchronous nature of the dynamics where the evolution of each local structure starts at different times and lasts for various durations. To address this, we propose a novel representation of dynamic graphs as temporal edge sequences associated with joining time of vertices (ToV) and timespan of edges (ToE). We also introduce a time-aware Transformer to embed the dynamic connections and ToEs into learned vertex representations, along with encoding time-sensitive information. Our approach outperforms the state-of-the-art in various graph mining tasks and is efficient for embedding large-scale dynamic graphs.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Information Systems
Lei Yang, Junzhong Jia, Hongcai Lin, Jiannong Cao
Summary: This paper focuses on the problem of Service Function Chain (SFC) scheduling in the dynamic 5G network environment. It formulates the problem as a mixed integer non-linear programming and proposes a reinforcement learning method to increase the success rate of SFC requests.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
