Article
Engineering, Civil
Pincan Zhao, Changle Li, Yuchuan Fu, Yilong Hui, Yao Zhang, Nan Cheng
Summary: This paper presents a blockchain-enabled conditional decentralized vehicular crowdsensing system that aims to balance system management, privacy preservation, and participants' quality of experience.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Can Zhang, Liehuang Zhu, Chang Xu, Kashif Sharif
Summary: Vehicular crowdsensing, widely used in smart cities, faces challenges such as privacy issues and data reliability. This study proposes a novel blockchain-based approach to address these challenges by providing privacy protection, reliable data storage, and fair rewards for data providers. Through theoretical analysis and experimental evaluations, the proposed method demonstrates significant computation and communication efficiency in achieving privacy, reliability, and fairness.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Zhengqiu Zhu, Xiao Wang, Yong Zhao, Sihang Qiu, Zhong Liu, Bin Chen, Fei-Yue Wang
Summary: This article introduces the application of blockchain technology in vehicular crowdsensing (VCS) systems, addressing the problems faced by centralized VCS frameworks and presenting potential directions for future research.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2022)
Article
Computer Science, Information Systems
Hao-Tian Wu, Yucong Zheng, Bowen Zhao, Jiankun Hu
Summary: In mobile crowdsensing, dishonest workers may upload false or malicious sensing data. To address this issue, an anonymous reputation management system based on dual blockchain architecture is proposed, utilizing ring signatures and Pedersen commitments for anonymous reputation score updates and verification.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Sizheng Fan, Hongbo Zhang, Zehua Wang, Wei Cai
Summary: In this paper, a blockchain-based federated learning system is implemented, and an incentive mechanism is proposed to establish a decentralized and transparent trading platform. Economic analysis is conducted to understand the behaviors of mobile devices, and two strategy models, namely the discrete strategy model and the continuous strategy model, are proposed. The interactions among non-cooperative mobile devices are formulated as a dynamic game, and the existence of Nash equilibrium for two different models is proven. Algorithms are proposed to achieve the equilibrium, and simulation results demonstrate their convergence and the effectiveness of the continuous strategy model in increasing mobile devices' payoffs by up to 128.1% compared to the discrete strategy model.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Qin Hu, Zhilin Wang, Minghui Xu, Xiuzhen Cheng
Summary: Mobile crowdsensing (MCS) utilizes the mobility of workers to help requestors accomplish sensing tasks more flexibly and at a lower cost. However, the large consumption of communication resources and high requirements on storage and computing capability hinder requestors with limited resources from using MCS. To address these challenges and promote the widespread application of MCS, we propose a novel MCS learning framework based on blockchain technology and federated learning, involving requestors, blockchain, edge servers, and mobile devices as workers.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Weizheng Wang, Yaoqi Yang, Zhimeng Yin, Kapal Dev, Xiaokang Zhou, Xingwang Li, Nawab Muhammad Faseeh Qureshi, Chunhua Su
Summary: Mobile crowdsensing (MCS) is an important approach that utilizes idle resources of portable devices to accomplish sensing tasks. Traditional MCS has security issues due to its reliance on centralized servers, and blockchain-based MCS systems have been proposed to address this. In this study, a secure, interactive, and fair blockchain-based MCS system called BSIF is proposed by integrating smart contracts and mobile devices. BSIF ensures the legitimacy and privacy of participants through identity verification and location privacy protection methods. The evaluation process is transferred to the requester side to reduce computation cost, and the Stackelberg game is used to achieve a dynamic balance between worker participation and requester rewards.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Yuntao Wang, Zhou Su, Jiliang Li, Ning Zhang, Kuan Zhang, Kim-Kwang Raymond Choo, Yiliang Liu
Summary: This paper proposes an energy blockchain-based secure PCP sharing scheme to improve the utility of EV users and renewable energy efficiency in PCP sharing networks.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Yuna Jiang, Jiawen Kang, Dusit Niyato, Xiaohu Ge, Zehui Xiong, Chunyan Miao, Xuemin Shen
Summary: The metaverse provides a virtual space for people to interact through digital avatars, but real-time rendering is a key challenge. This paper proposes a hierarchical game-theoretic CDC framework for metaverse services, particularly for vehicular metaverse. The framework utilizes idle resources from vehicles as CDC workers to handle intensive computation tasks.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Civil
Ruonan Zhao, Laurence T. Yang, Debin Liu, Xianjun Deng, Yijun Mo
Summary: Space-Air-Ground Integrated Vehicular Crowdsensing (SAGI-VCS) has great potential, but centralized implementation is vulnerable to attacks and lacks trust. Blockchain can solve the trust issue and incentivize vehicle participation, achieving better performance.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Chemistry, Analytical
Zhe Li, Xiaolong Liu, Yang Huang, Honglong Chen
Summary: This paper addresses the challenges of task assignment and privacy protection in vehicular crowdsensing. It proposes a User-Based Task Assignment (UBTA) mechanism that selects the smallest set of participants to minimize payment cost and introduces a privacy protection method based on differential privacy to safeguard user sensitive data. The efficacy of the proposed algorithm is demonstrated through theoretical analysis and simulation experiments.
Article
Automation & Control Systems
Can Zhang, Liehuang Zhu, Chang Xu
Summary: To solve parking issues, a Blockchain-based smart parking scheme named BSDP is proposed, which utilizes IIoT devices and VSNs to monitor parking spaces and traffic conditions and protects the privacy of drivers and VSN participants.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Shihong Zou, Jinwen Xi, Guoai Xu, Miao Zhang, Yueming Lu
Summary: This article proposes a new decentralized crowdsensing system called CrowdHB, which utilizes a hybrid blockchain architecture and smart contracts to ensure location privacy preservation and data quality while improving system performance. The proposed system also includes a location privacy-preserving optimization mechanism and an approach of consistency optimization to achieve a tradeoff between user privacy and system performance.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Civil
Rui Xing, Zhou Su, Qichao Xu, Ning Zhang, Tom H. Luan
Summary: This paper proposes a secure content delivery service for connected and autonomous trucks (CATs) based on coalition formation game, taking advantage of the high caching space and flexibility of CATs to reduce transmission delay in AVNs and protect security and privacy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Xuejiao Liu, Wei Chen, Yingjie Xia, Renhao Shen
Summary: This study proposes a secure vehicular crowdsensing scheme based on multi-authority attribute-based signature to achieve message authentication and privacy protection, as well as a multi-authority key management scheme to improve sensing efficiency. Performance analysis demonstrates the efficiency and effectiveness of the proposed schemes for vehicular crowdsensing applications.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Telecommunications
Ning Yang, Bangning Zhang, Guoru Ding, Yimin Wei, Guofeng Wei, Jian Wang, Daoxing Guo
Summary: This letter proposes an approach for specific emitter identification (SEI) using model-agnostic meta-learning, which achieves high accuracy with a limited number of labeled training samples. The approach is improved to be suitable for classifying electromagnetic signals from multiple types of equipments without requiring extensive retraining of the model structure. Experimental results using data from ZigBee devices and UAVs show that the proposed approach achieves an accuracy of over 90%, even when the training and testing tasks involve different types of devices.
IEEE COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Feng Shen, Zheng Wang, Guoru Ding, Kezhi Li, Qihui Wu
Summary: In this paper, the authors propose an approach to spectrum mapping that utilizes sparsity and compressed sensing. By optimizing the measurement matrix and using a 3D spatial subspace algorithm, they are able to recover the spectrum situation with reduced sampling and high mapping accuracy.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Engineering, Civil
Yilong Hui, Zhou Su, Tom H. Luan
Summary: This article establishes an intelligent multi-attribute service response framework in smart city to address the challenge of executing services with minimum cost based on user requirements and AVs statuses.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Quyuan Luo, Changle Li, Tom H. Luan, Weisong Shi
Summary: This article discusses the issue of offloading real-time computation tasks in vehicular edge computing. By considering the allocation of communication and computation resources, a multi-objective optimization algorithm is proposed to minimize the delay and cost. The simulation results demonstrate the effectiveness of this algorithm.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Lina Zhu, Yimin Zhou, Riheng Jia, Wanyi Gu, Tom Hao Luan, Minglu Li
Summary: The paper introduces a vehicle-mounted fault diagnosis system with low computational complexity and small data storage for real-time monitoring of vehicle status. The system utilizes feature selection algorithm and sliding window mechanism to minimize computational cost and reduce data storage requirements while ensuring the accuracy of fault diagnosis. Furthermore, the real-time fault diagnosis results can be shared with other vehicles in a cooperative intelligent transportation systems (C-ITS).
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Ruhan Liu, Jinkai Zheng, Tom H. H. Luan, Longxiang Gao, Yilong Hui, Yong Xiang, Mianxiong Dong
Summary: This paper investigates the optimal data transmission method for collaborative driving in autonomous vehicular networks (AVNs). Based on the publish/subscribe scheme of ROS, vehicles share sensing data and collaborate in real-time. The main challenge is to schedule the contending data flows and allocate resources efficiently.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Xuelian Cai, Luqiao Wang, Yilong Hui, Yue Chen, Wenwei Yue, Hui Wang, Yao Zhang, Nan Cheng, Changle Li
Summary: This study proposes a sensor redeployment scheme based on minimum exposure path (MEP) to optimize the coverage performance of directional sensor networks (DSNs). The minimum exposure path is obtained using a particle swarm optimization (MEP-PSO) algorithm, and the optimal deployment locations and dispatch sensors are determined using an MEP-based coverage optimization (MEP-CO) algorithm. The proposed scheme significantly improves the minimum exposure value (MEV) and coverage ratio of the monitoring area compared to existing algorithms.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yilong Hui, Gaosheng Zhao, Changle Li, Nan Cheng, Zhisheng Yin, Tom H. H. Luan, Xiao Xiao
Summary: In this paper, we propose a digital twins (DT) enabled on-demand matching scheme for multi-task federated learning in the heterogeneous vehicular networks (HetVNets). By considering the diversified requirements of task requesters (TRs) and the differentiated training capabilities of roadside units (RUs), we design a DT enabled on-demand matching architecture and a vehicle selection mechanism to determine customized model training strategies. Simulation results show that the proposed scheme outperforms conventional schemes in terms of training accuracy, performance-cost ratio (PCR), and task completion rate (TCR).
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Yilong Hui, Yuanhao Huang, Changle Li, Nan Cheng, Pincan Zhao, Rui Chen, Tom H. Luan
Summary: This article proposes an on-demand self-media data trading scheme in hetvnets, which designs a trading architecture considering both data caching services and data selling services based on blockchain and smart contracts. In the data caching phase, an iterative algorithm is used to obtain optimal strategies for media data producers (MDPs) and media data sellers (MDSs). In the data selling phase, an iteration-based mechanism helps MDSs dynamically determine data selling strategies.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Rui Chen, Lili Chang, Yilong Hui, Nan Cheng, Wei Zhang
Summary: With the widespread application of wireless networks, intelligent analysis of network behaviors is increasingly important. This paper proposes a topology inference algorithm based on network spatiotemporal features, which uses monitoring sensors to obtain the topology information of noncooperative wireless networks. The algorithm exploits neural networks and K-nearest neighbors for inference, improving accuracy.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Yilong Hui, Yi Qiu, Nan Cheng, Zhisheng Yin, Rui Chen, Kai Liang, Tom H. Luan
Summary: We propose a new scheme for content delivery in heterogeneous vehicular networks based on digital twin technology, which effectively addresses the challenges of frequent interactions and content distribution between vehicular users and roadside units. In this scheme, personalized content requirements are perceived by considering content popularity and relevance, and collaborative content requests are made with neighboring roadside units. Furthermore, through collaborative content recommendation and caching algorithms, each roadside unit can fully utilize the limited cache resources, improving content hit ratio and reducing delay.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yongjun Liu, Rui Chen, Yan Zhou, Mengjie Liu, Yilong Hui, Nan Cheng
Summary: Vehicular location information is important in intelligent transportation systems, and an Internet of Things (IoT)-based sensing system using RFID technology has been developed for accurate vehicle localization without relying on GNSS. The system utilizes virtual broadband multi-frequency continuous-wave transmission and phase extraction to achieve high-precision localization. By applying a genetic algorithm and modeling the localization problem as hyperbolic equations, the system can achieve localization accuracy below 5 cm.
IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION
(2023)
Article
Computer Science, Artificial Intelligence
Rui Chen, Jiameng Ning, Yu Lei, Yilong Hui, Nan Cheng
Summary: An increasing number of connected vehicles (CVs) and regular vehicles (RVs) driving together on the road is inevitable for future traffic development. To ensure safe and efficient traffic, accurate detection of traffic flow state is crucial. This study proposes a roadside radar and camera data fusion framework that utilizes real-time communication between CVs and roadside unit (RSU) to improve the accuracy of traffic flow state detection.
IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Mengqiu Tian, Changle Li, Yilong Hui, Nan Cheng, Wenwei Yue, Yuchuan Fu, Zhu Han
Summary: This paper studies the multiplexing of enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low-Latency Communications (URLLC) in a multi-UAV relay network. It proposes a hierarchical UAV-assisted eMBB/URLLC multiplexing scheduling framework and utilizes decomposition-relaxation-optimization algorithm and deep reinforcement learning algorithm to maximize eMBB data rates while meeting URLLC requirements.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
