Article
Computer Science, Information Systems
Haiyang Yu, Runkun Liu, Zhiheng Li, Yilong Ren, Han Jiang
Summary: This study focuses on balancing efficiency and coverage by establishing an RSU deployment strategy based on traffic demand. Simulation results show that covering 25% of the road segments with RSUs can serve most vehicles and reduce the delay of VANETs. Furthermore, road networks with high traffic demand require more RSUs to achieve the same effect, and early RSU investment is more cost effective.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Abir Mchergui, Tarek Moulahi
Summary: In this paper, a novel hybrid relay selection technique based on deep learning and reinforcement learning is proposed for VANET broadcasting. Experimental results show that the proposed technique outperforms other schemes in terms of success rate, saved rebroadcasts, and delay.
Review
Telecommunications
Suchi Johari, M. Bala Krishna
Summary: Vehicular ad hoc networks play a critical role in intelligent transportation systems, particularly in message delivery and protocols. TDMA MAC protocols address issues such as link failures and load imbalance in the network by reducing message collisions and ensuring secure message delivery.
VEHICULAR COMMUNICATIONS
(2021)
Article
Telecommunications
Abir Mchergui, Tarek Moulahi, Sherali Zeadally
Summary: Advancements in communications, smart transportation systems, and computer systems have opened up new possibilities for intelligent solutions in traffic safety and convenience. Artificial Intelligence (AI) is currently being utilized in the field of Vehicular Ad hoc NETworks (VANETs) to enhance conventional data-driven methods and improve passenger comfort, safety, and road experience.
VEHICULAR COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Deepak Choudhary, Roop Pahuja
Summary: This study proposes a solution for improving the performance of Transmission Control Protocols (TCP) in Vehicle Ad hoc Networks (VANETs) by introducing zone-based routing with consideration for mobility. A hybrid optimization algorithm (ABC) is used, which combines Ant Colony Optimization (ACO) and Artificial Bee Colony Optimization (ABCO), with link stability and residual energy as the basis of the fitness function. The effectiveness of the proposed method is evaluated using measures such as delivery ratio, time, and overhead, and compared with other algorithms.
JOURNAL OF BIG DATA
(2023)
Article
Chemistry, Analytical
Sofia Azam, Maryum Bibi, Rabia Riaz, Sanam Shahla Rizvi, Se Jin Kwon
Summary: Vehicular Ad-hoc network (VANET) is a technology with exciting prospects and significant security challenges. Despite various strategies proposed to detect network attacks, VANET is still susceptible to different attacks, especially Sybil attack. To address this issue, a novel collaborative framework based on majority voting is proposed to detect Sybil attack by ensembling individual classifiers.
Article
Computer Science, Hardware & Architecture
Guangbing Xiao, Haibo Zhang, Zhiyi Huang, Yawen Chen
Summary: This paper proposes a decentralized cooperative broadcasting protocol for Vehicle-to-Vehicle (V2V) communication, which allows vehicles to piggyback received messages in their routine broadcasts to help others recover lost traffic information. By introducing a bitmap data structure to record the receiving status of each vehicle, the protocol enables efficient detection of lost messages, estimation of wireless link quality, and achieves high reliability in message delivery.
Article
Computer Science, Information Systems
L. Ellen Funderburg, Huimin Ren, Im-Yeong Lee
Summary: VANETs are a type of Internet of Things system where vehicles communicate with each other and infrastructure to improve safety and quality of life. Security in VANETs requires vehicles to be accountable for accurate reporting and quick message security. The paper introduces a pairing-free signature scheme for VANETs to prevent identity forgery.
Article
Chemistry, Multidisciplinary
Rafiya Sohail, Yousaf Saeed, Abid Ali, Reem Alkanhel, Harun Jamil, Ammar Muthanna, Habib Akbar
Summary: Diabetes is a chronic disease that requires continuous management, and diabetic drivers are found to be the main cause of major road accidents. This research proposes a novel approach using wearable sensors, machine learning, and VANET technology to monitor the diabetic condition of drivers and reduce the accident rate. The performance evaluation shows that the random forest algorithm achieves the highest accuracy compared to other algorithms and previous approaches, ranging from 90.3% to 99.5%.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Electrical & Electronic
Sreelakshmi Pazhoor, Jesy Pachat, Anjana Ambika Mahesh, P. P. Deepthi, B. Sundar Rajan
Summary: In this work, a novel technique called index coded NOMA (IC-NOMA) is proposed, which combines NOMA and index coding to reduce the number of transmissions and improve spectral efficiency. Through detailed analytical studies, it is validated that the proposed transmission system provides improved spectral efficiency and power saving compared to conventional IC systems.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Alireza Aghabagherloo, Mahshid Delavar, Javad Mohajeri, Mahmoud Salmasizadeh, Bart Preneel
Summary: Vehicular ad-hoc networks (VANETs) play a crucial role in enhancing traffic safety and efficiency by providing a communication platform for real-time information sharing. This paper proposes a secure and efficient Conditional Privacy-Preserving Authentication (CPPA) scheme to address the security requirements of data authentication and privacy preservation in VANETS, with improved performance compared to existing schemes.
Article
Computer Science, Information Systems
Hamed Mosavat-Jahromi, Yue Li, Yuanzhi Ni, Lin Cai
Summary: This paper proposes a distributed and adaptive reservation based MAC protocol (DARP) to address the reliability and scalability issues of beacon broadcasting in VANETs. By analyzing protocol performance, parameters can be adjusted to reduce collision probability and enhance reliability and scalability.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Article
Computer Science, Information Systems
Azzam Mourad, Hanine Tout, Omar Abdel Wahab, Hadi Otrok, Toufic Dbouk
Summary: The article discusses the challenges of intrusion detection in Internet of Vehicles and vehicular networks, and proposes a vehicular-edge computing (VEC) fog-enabled scheme to offload intrusion detection tasks with minimal latency. The scheme aims to maximize offloading survivability while minimizing computation execution time and energy consumption.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Le Chang, Xia Deng, Jianping Pan, Yun Zhang
Summary: This article studies the problem of deploying edge servers in a metropolitan area. By analyzing the Shanghai Taxi Trace and building multiobjective optimization models, a heuristic multiobjective optimization method is proposed to address this problem. Numerical results demonstrate that this method achieves a desirable balance among delay, hand-offs, and cost.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Civil
Shengchu Wang, Xianbo Jiang
Summary: In this paper, a three-dimensional universal cooperative localizer (3D UCL) is proposed for vehicular ad-hoc networks (VANETs), and a 3D geographical information enhanced UCL (3D GIE-UCL) is developed by combining 3D UCL with a NLOS identification mechanism assisted by geographical information. Both 3D UCL and 3D GIE-UCL show significant improvement in positioning performance after the application of acceleration techniques.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Sheng Yue, Ju Ren, Jiang Xin, Deyu Zhang, Yaoxue Zhang, Weihua Zhuang
Summary: The paper explores the challenges of federated meta-learning in edge learning and proposes a new algorithm (NUFM) and resource allocation scheme to improve convergence speed and minimize time and energy costs.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Engineering, Civil
Ahmed Abdalrahman, Weihua Zhuang
Summary: This article proposes a differentiated pricing mechanism for a multiservice PEV charging infrastructure using model-free deep reinforcement learning. The mechanism adjusts service pricing to maximize facility utilization while ensuring service quality satisfaction.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Wen Wu, Mushu Li, Kaige Qu, Conghao Zhou, Xuemin Shen, Weihua Zhuang, Xu Li, Weisen Shi
Summary: This paper proposes a novel Split learning (SL) scheme called Cluster-based Parallel SL (CPSL) to reduce training latency by parallelizing device-side model training and sequentially training the whole AI model. A resource management algorithm is also proposed to consider device heterogeneity and network dynamics. Extensive simulation results demonstrate that the proposed solution greatly reduces training latency and adapts to network dynamics compared with existing SL benchmarks.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Editorial Material
Engineering, Electrical & Electronic
Weihua Zhuang
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
Article
Engineering, Electrical & Electronic
Yufeng Li, Qi Liu, Weihua Zhuang, Yiqing Zhou, Chenhong Cao, Jiangxing Wu
Summary: This article proposes a dynamic heterogeneous redundancy (DHR) scheme for connected automated vehicles (CAVs) to achieve both safety and security in the presence of functional failures or cyberattacks. The DHR architecture, employing multiple heterogeneous executors with the same function, ensures functional safety by providing redundancy and enhances security by detecting abnormal executors caused by cyberattacks. Test results on an automated bus demonstrate the effectiveness of the proposed DHR in enhancing both safety and security for CAVs.
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
Editorial Material
Engineering, Electrical & Electronic
Weihua Zhuang
Summary: The IEEE Vehicular Technology Society is excited for the upcoming 97th Annual Vehicular Technology Conference in Florence, Italy. The conference organizers and committee members are acknowledged for their efforts.
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
Editorial Material
Engineering, Electrical & Electronic
Weihua Zhuang
Summary: This time of year is significant for the IEEE Vehicular Technology Society (VTS) as it holds the VTS Award ceremony during the 98th Annual IEEE Vehicular Technology Conference in Hong Kong (VTC2023-Fall) and brings professionals together at the 2023 IEEE Vehicle Power and Propulsion Conference in Milan, Italy.
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
Article
Computer Science, Information Systems
Kaige Qu, Weihua Zhuang, Wen Wu, Mushu Li, Xuemin Shen, Xu Li, Weisen Shi
Summary: This paper focuses on deep neural network (DNN)-based classification tasks and investigates how to improve the confidence level and delay performance of DNN inference through device-edge collaboration. By developing a stochastic cumulative DNN inference scheme and a computation-efficient DNN model deployment strategy, an adaptive device-edge collaboration scheme is proposed to support cumulative DNN inference for multiple devices. Simulation results demonstrate the effectiveness of this scheme.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Automation & Control Systems
Hiroaki Mukaidani, Shunpei Irie, Hua Xu, Weihua Zhuang
Summary: In this paper, the authors discuss linear-quadratic mean-field social control problems for a specific class of stochastic systems with ordinary and delay control inputs. They introduce a stabilization problem using a memoryless static output feedback (SOF) strategy and use the guaranteed cost control theory to minimize the upper bound of the cost function. The study reveals that minimizing the upper bound of the cost function is not achievable with only a delay control input. They also prove the impossibility of implementing a mean-field SOF strategy and establish the necessary conditions for sub-optimality using stochastic cross-coupled matrix equations (SCCMEs) and the Karush-Kuhn-Tucker condition. Lastly, the authors investigate the performance and usefulness of their proposed strategy using an order-reduced scheme based on the direct method.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Computer Science, Information Systems
Wei Quan, Ziheng Xu, Mingyuan Liu, Nan Cheng, Gang Liu, Deyun Gao, Hongke Zhang, Xuemin Shen, Weihua Zhuang
Summary: This paper presents a survey on the recent research in AI-driven packet forwarding with programmable data plane (PDP). Two representative frameworks of packet forwarding, traditional AI-driven forwarding and PDP-assisted forwarding, are described. The capacity of packet forwarding under these frameworks is evaluated in terms of delay, throughput, security, and reliability. The paper also identifies three directions in the development of AI-driven packet forwarding and highlights challenges and issues in future research.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Article
Computer Science, Information Systems
Xiaozhen Lu, Liang Xiao, Pengmin Li, Xiangyang Ji, Chenren Xu, Shui Yu, Weihua Zhuang
Summary: Sixth-generation (6G) cellular systems are vulnerable to PHY-layer attacks and privacy leakage due to large-scale networks and time-sensitive applications. Optimized security schemes suffer performance degradation in 6G systems, and reinforcement learning (RL) algorithms can enhance security against smart attacks without relying on attack models. This article provides a comprehensive survey on RL-based 6G PHY cross-layer security and privacy protection.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Review
Computer Science, Interdisciplinary Applications
Xuemin (Sherman) Shen, Jie Gao, Mushu Li, Conghao Zhou, Shisheng Hu, Mingcheng He, Weihua Zhuang
Summary: The sixth generation (6G) networks are expected to revolutionize communication by enabling immersive experiences through the integration of extended reality, holography, and haptics. However, the high demand for data transmission rate and stringent requirements for latency and reliability pose challenges for 6G networks to support immersive communications. This survey article presents the prospects and challenges of immersive communications in 6G networks, along with emerging solutions to address these challenges.
FRONTIERS IN COMPUTER SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Mushu Li, Jie Gao, Conghao Zhou, Xuemin Shen, Weihua Zhuang
Summary: In this article, a novel approach for content caching and delivery in mobile virtual reality (VR) video streaming is presented. The proposed approach aims to maximize VR video streaming performance by proactively caching popular VR video chunks and adaptively scheduling computing resources at an edge server based on user and network dynamics. The approach includes a scalable content placement scheme and a machine learning-assisted VR video delivery scheme to improve video delivery efficiency and reduce frame missing rate.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2023)
Article
Computer Science, Information Systems
Qi Cheng, Hangguan Shan, Weihua Zhuang, Tony Q. S. Quek, Zhaoyang Zhang, Fen Hou
Summary: This study explores the cooperation between e-commerce platform companies and network operators as virtual network operators in China and proposes an incentive mechanism based on mobile data reward to maximize profits for network players. It introduces a three-stage static Stackelberg game and a deep Q-network based algorithm to derive optimal strategies. Simulation results demonstrate the impact of system parameters on game players and social welfare.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Automation & Control Systems
Hiroaki Mukaidani, Shunpei Irie, Hua Xu, Weihua Zhuang
Summary: This study investigates a static output feedback (SOF) strategy for robust incentive Stackelberg games with a large population in mean-field stochastic systems. By introducing a low-dimensional approximation algorithm and restructuring strategies, a centralized strategy can be achieved to reduce the high dimensionality of the design process. The research shows that the equilibrium values difference between using the centralized SOF strategy and using the low-dimensional approximation SOF strategy is O(root epsilon) = O(1/root N), where N represents the population size.
IEEE CONTROL SYSTEMS LETTERS
(2022)
