Article
Engineering, Electrical & Electronic
Wenqi Zhou, Junjuan Xia, Fasheng Zhou, Lisheng Fan, Xianfu Lei, Arumugam Nallanathan, George K. Karagiannidis
Summary: This paper investigates a multiuser cache-enabled vehicular mobile edge computing (MEC) network, and proposes a solution to the critical challenge of optimizing the system design and performance by maximizing the profit of the edge server (ES) and jointly exploiting caching and computing resources.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Yu Wu, Xuming Fang, Chunbo Luo, Geyong Min
Summary: The challenge of content dissemination in vehicular networks is addressed by introducing edge precaching technology and platoon-based vehicular networks. An intelligent deep reinforcement learning (DRL)-based content precaching scheme is proposed to improve reliability and latency performance.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Chemistry, Multidisciplinary
Zhaohui Luo, Minghui Liwang
Summary: This paper proposes an intelligent caching strategy that takes into account vehicle mobility, time-varying content popularity, and backhaul capability to improve the quality of experience (QoE) for vehicle users. By using deep reinforcement learning techniques, the video content caching problem is effectively solved and the proposed strategy demonstrates its effectiveness in experiments.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Hardware & Architecture
Lei Liu, Chen Chen, Qingqi Pei, Sabita Maharjan, Yan Zhang
Summary: Vehicular Edge Computing (VEC) is a promising solution that pushes computational and storage resources to the edge of networks, enabling low latency and reduced bandwidth consumption for vehicular users. Research in VEC includes an overview, applications, research topics, literature review, and future directions.
MOBILE NETWORKS & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
The-Vinh Nguyen, Anh-Tien Tran, Nhu-Ngoc Dao, Hyeonjoon Moon, Sungrae Cho
Summary: This study provides a comprehensive assessment of mobile edge caching, including an overview of caching techniques, an investigation of performance indicators, and description of common use cases and applications. It also discusses the challenges and future directions of edge caching.
INFORMATION FUSION
(2023)
Article
Telecommunications
Hao Zhou, Melike Erol-Kantarci, H. Vincent Poor
Summary: In this paper, a deep transfer reinforcement learning (DTRL) scheme is proposed for 5G network slicing to improve resource allocation performance. Through comparative experiments, DTRL shows lower latency and higher throughput.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2022)
Article
Chemistry, Analytical
Salahadin Seid Musa, Marco Zennaro, Mulugeta Libsie, Ermanno Pietrosemoli
Summary: This paper proposes a mobility-aware Information-Centric Network with proactive caching scheme to provide delay-sensitive services on IoV networks. Research shows that the proposed scheme outperforms related caching schemes in terms of latency and cache hits.
Article
Engineering, Civil
Cong Wang, Chen Chen, Qingqi Pei, Ning Lv, Houbing Song
Summary: Vehicular Named Data Networking (VNDN) has gained popularity as a candidate solution to support various applications of vehicular communications. It aims to improve data dissemination efficiency by addressing issues such as IP addressing, unstable connectivity, and diversified service requirements. In-vehicle caching is proposed as an effective edge computing paradigm to alleviate the traffic burden on base stations. However, designing a fair caching strategy remains challenging due to selfish behaviors of individuals.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Zhen Li, Chao Yang, Xumin Huang, WeiLiang Zeng, Shengli Xie
Summary: In vehicular edge computing networks, edge service caching is a promising technology for supporting delay sensitive applications. This paper proposes a collaborative task offloading and service caching replacement scheme, named CoOR, which considers task processing cooperation between adjacent RSUs and service caching replacement for vehicles. An iterative algorithm combined with Gibbs sampling and deep reinforcement learning (DRL) is developed to find optimal decisions for the problem of task offloading and service caching coupling. Extensive simulation results show that the proposed scheme outperforms traditional baselines.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Hardware & Architecture
Rudzidatul Akmam Dziyauddin, Dusit Niyato, Nguyen Cong Luong, Ahmad Ariff Aizuddin Mohd Atan, Mohd Azri Mohd Izhar, Marwan Hadri Azmi, Salwani Mohd Daud
Summary: The paper discusses the adoption of Cloud Computing in automotive industries, the challenges of end-to-end latency, and the consideration of computing capability at the edge of vehicular network. It outlines the aspects of Vehicular Edge Network, particularly Vehicular Edge Computing, and reviews existing approaches in solving ComOf and CachDel problems. Security aspects in ComOf and CachDel are also critically discussed, along with key challenges, open issues, and future works in VEC.
Article
Engineering, Electrical & Electronic
Peng Liu, Yifan Zhang, Tingting Fu, Jia Hu
Summary: This paper explores the use of vehicles as mobile edge caching nodes to form a local cloud, providing popular content for nearby users via 6G communication. By predicting vehicle driving trajectories and estimating the popularity of content in urban areas, a scoring system is designed to compare user satisfaction and computational efficiency of different algorithms. The proposed scheme outperforms conventional methods by offering a cost-efficient content allocation solution with lower delay.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Yanfei Lu, Dengyu Han, Xiaoxuan Wang, Qinghe Gao
Summary: In this research, Vehicular Edge Computing is applied in vehicular scenarios to provide on-demand computational resource access. The study focuses on dynamic cooperative task caching between RSUs and adapting to time-varying wireless environment using the DDPG algorithm. The proposed DDPG-OCWB algorithm improves convergence performance.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Feng Zeng, Kanwen Zhang, Lin Wu, Jinsong Wu
Summary: In this paper, the efficient caching mechanism for supporting data in vehicular edge computing (VEC) is studied. The acquisition ways of the supporting data and the caching collaboration between VEC servers are analyzed using the software defined network (SDN) based VEC framework. The VEC coverage is divided into dense and ordinary areas based on the density of the requesting vehicles. Edge servers are clustered into multiple groups based on K-means++ algorithm, considering the similarity of the requested data and the distance between servers. An efficient edge-cloud collaborative caching strategy is proposed, which reduces the delay of data migration during task execution.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Zhongzheng Tang, Nuo Yu, Xiaohua Jia, Xiaodong Hu
Summary: Edge caching is an effective strategy to reduce the traffic load in mobile core networks by caching popular content at the edge of mobile networks. Coded multicast can be used to improve transmission efficiency for data transmission from base stations to user equipment. This paper addresses the Data Placement and Transmission Scheduling (DPTS) problem for cache-aided coded multicast in mobile edge networks. It proposes algorithms, including an Iterative Relaxation Linear Programming (IRLP) algorithm, to minimize the total cost of data download and transmission.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Ruizhi Wu, Bo Li
Summary: Considering the rapid growth of business types and the characteristics of delay-sensitive tasks in vehicular networks, this paper proposes a vehicular network architecture that allows for heterogeneous tasks to be processed on roadside units co-located with MEC servers. To optimize task completion delay and energy consumption, a joint optimization problem is formulated and solved using a grey wolf optimizer-joint optimization algorithm. Experimental results show significant performance improvement compared to other algorithms.
JOURNAL OF SUPERCOMPUTING
(2023)
Letter
Dermatology
Kai Sun, Xuemin Shen
PHOTODERMATOLOGY PHOTOIMMUNOLOGY & PHOTOMEDICINE
(2023)
Article
Dentistry, Oral Surgery & Medicine
Wei Liu, Qianqian Zhang, Xuemin Shen, Zhexuan Bao
Summary: Oral lichen planus (OLP) and pemphigus vulgaris (PV) are two common inflammatory mucocutaneous diseases of immune-based etiology. Evidence suggests that regulatory T (Treg) cells may play a role in the pathogenesis of OLP and PV. This study found that Treg levels were significantly higher in OLP patients compared to healthy controls, while Treg levels were significantly lower in PV patients compared to healthy controls.
JOURNAL OF DENTAL SCIENCES
(2023)
Article
Dentistry, Oral Surgery & Medicine
Wei Liu, Meng Li, Xinzhong Zhang, Zengtong Zhou, Zhengyu Shen, Xuemin Shen
Summary: This study aimed to investigate the genetic associations between SNPs in 6 cytokines (IFN-g, IL-18, TGFb1, IL-13, IL-2, IL-4) and OLP susceptibility. A significant association was found between IFN-g (874A/T) and IL-18 (137G/C) polymorphisms with OLP. A marginally significant association was found between TGFb1 (509C/T) polymorphism and OLP. However, no significant associations were found for IL-1b (3954C/T), IL-2 (330T/G), IL-4 (590C/T), and IL-18 (607C/A) polymorphisms with OLP.
JOURNAL OF DENTAL SCIENCES
(2023)
Article
Dentistry, Oral Surgery & Medicine
Wei Liu, Huan Shi, Zengtong Zhou, Chenping Zhang, Xuemin Shen
Summary: There is a need for noninvasive biomarkers to diagnose oral potentially malignant disorders (OPMD). Many studies have investigated over 20 miRNAs in the saliva of OPMD patients. However, it is uncertain which miRNAs provide better discrimination power for the diagnosis of OPMD onset and progression.
JOURNAL OF DENTAL SCIENCES
(2023)
Letter
Oncology
Xi Yang, Lijun Liu, Xuemin Shen, Linjun Shi, Wei Liu
Summary: Increasing evidence suggests that lncRNAs act as ceRNAs by competitively binding miRNAs, and play important roles in the biological processes of TSCC. This study summarizes the ceRNA regulatory networks involving lncRNA/miRNA/mRNA axes in TSCC. Dysregulated profiles of 33 lncRNAs and 31 miRNAs were identified and found to be involved in various cancer-associated phenotypes, including cell proliferation, apoptosis, invasion, migration, and chemoresistance. The functional inactivation of ceRNAs in tumor cells may provide novel diagnostic and therapeutic strategies for TSCC.
Editorial Material
Oncology
Shijian Zhang, Xinyi Han, Mingyi Wang, Xuemin Shen
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)
Article
Computer Science, Information Systems
Jianbing Ni, Man Ho Au, Wei Wu, Xiapu Luo, Xiaodong Lin, Xuemin Shen
Summary: A dual-anonymous off-line electronic cash scheme is proposed using the BBS+ signature algorithm, which ensures secure payment in mobile commerce.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Ruoyu Su, Zijun Gong, Cheng Li, Xuemin Shen
Summary: Space-air-ground-sea integrated network, a promising networking paradigm for 6G communications, combines satellite, aerial, terrestrial, and marine networks. This paper presents a method for efficient target localization in the ocean using a mobile underwater acoustic array network and linear frequency modulated (LFM) signals. The method utilizes propagation delay and the Doppler effect to estimate the position and velocity of the moving target, achieving high accuracy with low computational complexity. Performance evaluation shows that the proposed method outperforms the least squares based approach, approaching the Cramer-Rao lower bound (CRLB) within two iterations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Cheng Huang, Wei Wang, Dongxiao Liu, Rongxing Lu, Xuemin Shen
Summary: This paper proposes a new personalized car insurance scheme using a consortium blockchain to achieve privacy preservation and transparency. Insurance companies can deploy insurance contracts on the blockchain to support public verification of data collection/processing. A verifiable and privacy-preserving driving behavior evaluation protocol is designed using partially homomorphic encryption and zero-knowledge proof techniques. Third-party auditors are authorized to audit encrypted driving data on the contracts to resist fraud attacks. The proposed scheme guarantees unbiased collection of driving data and security analysis and a proof-of-concept prototype is provided.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Peiyu Cheng, Tong Zhao, Mingming Chen, Sixue Chen, Xuemin Shen, Yuan Liu, Shikuan Yang, Zhanguo Chen, Xiuxiu Dong, Quan Wang, Dawei Cao
Summary: Improved perovskite CH3NH3PbI3 thin films were grown through Co-based ZIF-67 additive assisted Co ion doping. These thin films exhibit low grain boundaries, low defect states, and improved structural stabilities. The performance and stability of photodetectors based on CH3NH3Pb0.98Co0.02I3 thin films were enhanced, demonstrating the positive role of suppressing defect states.
ADVANCED OPTICAL MATERIALS
(2023)
Article
Computer Science, Information Systems
Wanting Yang, Hongyang Du, Zi Qin Liew, Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Xuefen Chi, Xuemin Shen, Chunyan Miao
Summary: This paper mainly introduces that the sixth-generation (6G) wireless networks will shift from a traditional architecture that focuses solely on a high transmission rate to a new architecture that is based on the intelligent connection of everything, and Semantic communication (SemCom) is predicted to become a new core paradigm in 6G. The paper provides a holistic review of the fundamentals of SemCom, its applications in 6G networks, and the existing challenges and open issues with insights for further in-depth investigations.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(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
Sijing Duan, Dan Wang, Ju Ren, Feng Lyu, Ye Zhang, Huaqing Wu, Xuemin Shen
Summary: This paper provides a comprehensive survey on distributed artificial intelligence (DAI) empowered by end-edge-cloud computing (EECC). It explores the benefits of the EECC paradigm in supporting distributed AI, introduces fundamental technologies for distributed AI, and discusses optimization technologies empowered by EECC for distributed training and inference. It also addresses security and privacy threats in the DAI-EECC architecture and reviews defense technologies. Furthermore, it presents promising applications enabled by DAI-EECC and highlights research challenges and open issues.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Article
Computer Science, Information Systems
Cheng-Xiang Wang, Xiaohu You, Xiqi Gao, Xiuming Zhu, Zixin Li, Chuan Zhang, Haiming Wang, Yongming Huang, Yunfei Chen, Harald Haas, John S. Thompson, Erik G. Larsson, Marco Di Renzo, Wen Tong, Peiying Zhu, Xuemin Shen, H. Vincent Poor, Lajos Hanzo
Summary: 5G has been commercially deployed, providing new services and improved user experiences to users, and offering novel opportunities to various industries. However, it still faces challenges, leading to research on 6G wireless communication systems by international organizations. This paper comprehensively presents the vision, technical requirements, and application scenarios of 6G, critically evaluates its network architecture and key technologies, introduces existing testbeds and advanced verification platforms, and identifies future research directions and open challenges.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)