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学者姓名：林志坚
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Abstract ：
Mobile edge caching (MEC) has emerged as a promising and economical solution to complement conventional infrastructure caching. Nonetheless, the vulnerability of vehicle-to-vehicle (V2V) links causes connection loss and limits data exchange. On the other hand, the traditional content popularity-based request model would lead to lower cache hit ratios and increased content retrieval times. To tackle this issue, a novel scheme of MEC-assisted public vehicular network is proposed in this study, where the random linear network coding (RLNC) based caching strategy is applied to allow public vehicles to simultaneously obtain coded blocks from multiple vehicles and infrastructures on the move. Besides, a content request model that considers content popularity, historical interest, and social attributes is explored. A cost minimization problem is formulated under the proposed scheme, which is a highly non-trivial stochastic problem. To this end, the data volume of V2V offloading is obtained by a divide and conquer (DC) algorithm, and then the caching strategy is derived by a heuristic-based algorithm. Finally, extensive simulations show that the proposed content model can achieve a higher local offloading ratio and the proposed scheme has a much lower cost compared to the baselines.
Keyword ：
Content request model Content request model Mobile edge caching Mobile edge caching Public vehicular networks Public vehicular networks V2V offloading V2V offloading
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| GB/T 7714 | Chen, Xiaopei , Lin, Zhijian , Wu, Wenhao et al. Cost-Efficient and Preference-Aware Mobile Edge Caching in Public Vehicular Networks [J]. | MOBILE NETWORKS & APPLICATIONS , 2025 . |
| MLA | Chen, Xiaopei et al. "Cost-Efficient and Preference-Aware Mobile Edge Caching in Public Vehicular Networks" . | MOBILE NETWORKS & APPLICATIONS (2025) . |
| APA | Chen, Xiaopei , Lin, Zhijian , Wu, Wenhao , Chen, Feng , Chen, Pingping . Cost-Efficient and Preference-Aware Mobile Edge Caching in Public Vehicular Networks . | MOBILE NETWORKS & APPLICATIONS , 2025 . |
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Mobile edge caching (MEC) has grown substantially with the rapid development in scale and complexity of data traffic. By exploiting the expansive coverage of autonomous aerial vehicles (AAVs), MEC enables services for massive vehicle users (VUs) simultaneously, which is promising for enhancing network transmission efficiency. Nonetheless, due to challenges arising from the timeliness and freshness of content services caused by AAVs' limited endurance and airborne capacity, caching strategy considering the real-time of content in large-scale dynamic Internet of Vehicles (IoV) environments remains open. With the above consideration, in this article, the cache refreshing cycle and content placement are jointly optimized in the cache-enabled AAV-assisted vehicular integrated networks (CAVINs) to minimize the content Age of Information (AoI) and energy consumption of the macro AAV. Since the joint optimization problem is variational coupled with nonconvex binary constraints, it is decoupled and solved by a double-iteration method. Specifically, the optimal cache refreshing cycle is derived in semi-closed form with the Karush-Kuhn-Tucker (KKT) conditions. The locally optimal solution of the content placement is obtained through successive convex approximation (SCA). Simulation results corroborate the effectiveness and superiority of the proposed scheme.
Keyword ：
Age of Information (AoI) Age of Information (AoI) Autonomous aerial vehicles Autonomous aerial vehicles Complexity theory Complexity theory Energy consumption Energy consumption Energy efficiency Energy efficiency Information age Information age Internet of Vehicles Internet of Vehicles Internet of Vehicles (IoV) Internet of Vehicles (IoV) mobile edge caching (MEC) mobile edge caching (MEC) Optimization Optimization Real-time systems Real-time systems Simulation Simulation unmanned aerial vehicles (AAVs)-assisted networks unmanned aerial vehicles (AAVs)-assisted networks Vehicle dynamics Vehicle dynamics
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| GB/T 7714 | Xiao, Yang , Lin, Zhijian , Cao, Xiaoxiao et al. AoI Energy-Efficient Edge Caching in AAV-Assisted Vehicular Networks [J]. | IEEE INTERNET OF THINGS JOURNAL , 2025 , 12 (6) : 6764-6774 . |
| MLA | Xiao, Yang et al. "AoI Energy-Efficient Edge Caching in AAV-Assisted Vehicular Networks" . | IEEE INTERNET OF THINGS JOURNAL 12 . 6 (2025) : 6764-6774 . |
| APA | Xiao, Yang , Lin, Zhijian , Cao, Xiaoxiao , Chen, Youjia , Lu, Xiaoqiang . AoI Energy-Efficient Edge Caching in AAV-Assisted Vehicular Networks . | IEEE INTERNET OF THINGS JOURNAL , 2025 , 12 (6) , 6764-6774 . |
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Abstract ：
针对车联网计算卸载需求量大及车辆网络拓扑变化随机性强的问题，本文提出一种基于邻域跟随的车辆多跳分簇方法，并采取多指标综合加权的方式研究其稳定性特征. 现有针对车辆分簇的研究方案普遍存在指标单一化、分簇机制局限于单跳或固定跳数、分簇效率低及缺少簇头替换机制等问题. 鉴于邻域跟随策略稳定性较优且分簇效率较高等特性，本文提出车辆基于邻居节点内综合指标最优准则选择稳定性最好的节点跟随方案，通过去环和剪枝算法使得车辆的跟随结构规范且扁平化，进而形成一个稳定性更高的车辆簇，并利用主从簇头和簇维护机制增强车辆簇的鲁棒性. 仿真结果表明，与现有的车辆分簇方法相比，所提算法在簇稳定性和分簇效率上均具有较好的性能.
Keyword ：
分簇效率 分簇效率 多跳分簇 多跳分簇 状态转移 状态转移 组网稳定性 组网稳定性 车联网 车联网 邻域跟随 邻域跟随
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| GB/T 7714 | 林志坚 , 吴文浩 , 陈小培 et al. 基于邻域跟随的车联网多跳分簇稳定性研究 [J]. | 电子学报 , 2024 . |
| MLA | 林志坚 et al. "基于邻域跟随的车联网多跳分簇稳定性研究" . | 电子学报 (2024) . |
| APA | 林志坚 , 吴文浩 , 陈小培 , 曾泽雄 , 林永航 , 陈平平 . 基于邻域跟随的车联网多跳分簇稳定性研究 . | 电子学报 , 2024 . |
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In view of the problems of high demand of computation offloading in vehicular networks and the random⁃ ness of topology variation of vehicular networks, this paper proposes a vehicular multi-hop clustering scheme based on neighbor following and investigates its stability by multiple indicators. Existing research offers various vehicular clustering schemes, but they suffer from issues such as single indicator, being limited to a single hop or fixed number of hops, low clustering efficiency, and lacking a mechanism for cluster head replacement. As the neighbor following strategy has better stability and higher clustering efficiency, in the scheme designed in this paper, vehicles should follow the most stable vehi⁃ cle based on the comprehensive indicators within neighboring nodes. The de-ringing and pruning algorithms are used to standardize and flatten the following structure of vehicles, forming a more stable vehicular cluster. The master-slave cluster header and the cluster maintenance mechanism are employed to enhance the robustness of vehicular cluster. Simulation re⁃ sults show that the proposed algorithm outperforms existing methods in terms of cluster stability and clustering efficiency. © 2024 Chinese Institute of Electronics. All rights reserved.
Keyword ：
Clustering algorithms Clustering algorithms Efficiency Efficiency Stability Stability
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| GB/T 7714 | Lin, Zhi-Jian , Wu, Wen-Hao , Chen, Xiao-Pei et al. Research on the Stability of Multi-Hop Clustering Based on Neighbor Following Method in Vehicular Networks [J]. | Acta Electronica Sinica , 2024 , 52 (4) : 1260-1268 . |
| MLA | Lin, Zhi-Jian et al. "Research on the Stability of Multi-Hop Clustering Based on Neighbor Following Method in Vehicular Networks" . | Acta Electronica Sinica 52 . 4 (2024) : 1260-1268 . |
| APA | Lin, Zhi-Jian , Wu, Wen-Hao , Chen, Xiao-Pei , Zeng, Ze-Xiong , Lin, Yong-Hang , Chen, Ping-Ping . Research on the Stability of Multi-Hop Clustering Based on Neighbor Following Method in Vehicular Networks . | Acta Electronica Sinica , 2024 , 52 (4) , 1260-1268 . |
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Vehicular fog computing (VFC) that supports inter-vehicular task offloading emerges as a promising complement to handle the explosive growth of computation-intensive tasks in Intelligent Transportation Systems (ITS). Nonetheless, as the fog access points (F-APs) in crowed areas are often overloaded, the conventional single F-AP VFC may become incompetent and energy-inefficient. To tackle the issue, a novel scheme of non-orthogonal multiple access (NOMA)-enabled multi-F-AP VFC with partial offloading is proposed in this work. However, the corresponding energy minimization turns out to be a highly non-trivial non-linear mixed-integer programming problem. To this end, the optimal power allocation is derived by exploiting monotonicity while good task splitting ratio and user association are found through successive convex approximation (SCA)-based interior-point method and game theoretic approach, respectively. Extensive simulations based on MATLAB show that, in the considered scenarios, the proposed scheme can fulfill a more balanced offloading and better exploit the available computing resources, thereby leading to an approximately 30% energy consumption reduction compared to the baselines.
Keyword ：
energy consumption energy consumption Non-orthogonal multiple access (NOMA) Non-orthogonal multiple access (NOMA) partial offloading partial offloading vehicular fog computing (VFC) vehicular fog computing (VFC)
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| GB/T 7714 | Lin, Zhijian , Chen, Xiaopei , He, Xiaofan et al. Energy-Efficient Cooperative Task Offloading in NOMA-Enabled Vehicular Fog Computing [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (7) : 7223-7236 . |
| MLA | Lin, Zhijian et al. "Energy-Efficient Cooperative Task Offloading in NOMA-Enabled Vehicular Fog Computing" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 25 . 7 (2024) : 7223-7236 . |
| APA | Lin, Zhijian , Chen, Xiaopei , He, Xiaofan , Tian, Daxin , Zhang, Qingsong , Chen, Pingping . Energy-Efficient Cooperative Task Offloading in NOMA-Enabled Vehicular Fog Computing . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (7) , 7223-7236 . |
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Anomaly detection is represented as an unsupervised learning to identify deviated images from normal images. In general, there are two main challenges of anomaly detection tasks, i.e., the class imbalance and the unexpectedness of anomalies. In this paper, we propose a multiresolution feature guidance method based on Transformer named GTrans for unsupervised anomaly detection and localization. In GTrans, an Anomaly Guided Network (AGN) pre-trained on ImageNet is developed to provide surrogate labels for features and tokens. Under the tacit knowledge guidance of the AGN, the anomaly detection network named Trans utilizes Transformer to effectively establish a relationship between features with multiresolution, enhancing the ability of the Trans in fitting the normal data manifold. Due to the strong generalization ability of AGN, GTrans locates anomalies by comparing the differences in spatial distance and direction of multi-scale features extracted from the AGN and the Trans. Our experiments demonstrate that the proposed GTrans achieves state-of-the-art performance in both detection and localization on the MVTec AD dataset. GTrans achieves image-level and pixel-level anomaly detection AUROC scores of 99.0% and 97.9% on the MVTec AD dataset, respectively.
Keyword ：
Anomaly detection Anomaly detection Deep learning Deep learning Knowledge distillation Knowledge distillation Transformer Transformer
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| GB/T 7714 | Yan, Shuting , Chen, Pingping , Chen, Honghui et al. Multiresolution feature guidance based transformer for anomaly detection [J]. | APPLIED INTELLIGENCE , 2024 , 54 (2) : 1831-1846 . |
| MLA | Yan, Shuting et al. "Multiresolution feature guidance based transformer for anomaly detection" . | APPLIED INTELLIGENCE 54 . 2 (2024) : 1831-1846 . |
| APA | Yan, Shuting , Chen, Pingping , Chen, Honghui , Mao, Huan , Chen, Feng , Lin, Zhijian . Multiresolution feature guidance based transformer for anomaly detection . | APPLIED INTELLIGENCE , 2024 , 54 (2) , 1831-1846 . |
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| GB/T 7714 | Yang, Jianjie , Lin, Zhijian , Chen, Yingyang et al. Game-based computation offloading and resource allocation in stochastic geometry-modeling vehicular networks [J]. | SCIENCE CHINA-INFORMATION SCIENCES , 2024 , 67 (12) . |
| MLA | Yang, Jianjie et al. "Game-based computation offloading and resource allocation in stochastic geometry-modeling vehicular networks" . | SCIENCE CHINA-INFORMATION SCIENCES 67 . 12 (2024) . |
| APA | Yang, Jianjie , Lin, Zhijian , Chen, Yingyang , Lu, Xiaoqiang , Fang, Yi . Game-based computation offloading and resource allocation in stochastic geometry-modeling vehicular networks . | SCIENCE CHINA-INFORMATION SCIENCES , 2024 , 67 (12) . |
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With the advancement of the Internet of Vehicles (IoV), delay-sensitive vehicular applications have flourished. Among them, the autonomous driving technology is a focal point. For autonomous driving vehicles, efficiently and timely processing the ever-increasing data is critical. In real traffic scenes, the task-processing efficiency is closely related to the traffic flows. However, the traffic flow modeling is always ignored or considered roughly in the most existing studies. For this issue, a traffic model based on a stochastic geometry framework is proposed to simulate a real traffic environment of autonomous driving vehicles. To reduce the cost of processing tasks, a distributed computation offloading scheme based on mobile edge computing (MEC) is proposed by soliciting nearby vehicles and roadside units (RSUs) with rich computing resources. For the average cost minimization optimization problem, we divide the NP-hard problem into several sub-problems and take advantage of the Lagrange multiplier with KKT constraints to solve by optimizing task splitting ratios. We compare the proposed traffic model with some common ones and also consider the pros and cons of different computation offloading strategies. Simulation results show that the proposed strategy outperforms other benchmarks and the proposed modeling method is rational.
Keyword ：
Autonomous vehicles Autonomous vehicles Computational modeling Computational modeling Costs Costs distributed computation distributed computation Geometry Geometry mobile edge computing mobile edge computing Servers Servers stochastic geometry stochastic geometry Stochastic processes Stochastic processes Task analysis Task analysis Vehicular network Vehicular network
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| GB/T 7714 | Yang, Jianjie , Chen, Yingyang , Lin, Zhijian et al. Distributed Computation Offloading in Autonomous Driving Vehicular Networks: A Stochastic Geometry Approach [J]. | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES , 2024 , 9 (1) : 2701-2713 . |
| MLA | Yang, Jianjie et al. "Distributed Computation Offloading in Autonomous Driving Vehicular Networks: A Stochastic Geometry Approach" . | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 9 . 1 (2024) : 2701-2713 . |
| APA | Yang, Jianjie , Chen, Yingyang , Lin, Zhijian , Tian, Daxin , Chen, Pingping . Distributed Computation Offloading in Autonomous Driving Vehicular Networks: A Stochastic Geometry Approach . | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES , 2024 , 9 (1) , 2701-2713 . |
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The rapid growth in vehicle data fosters the development of vehicular computational offloading. By exploiting the superiority of non-orthogonal multiple access (NOMA) in the offloading process, NOMA-enabled vehicular computation offloading enables collaborative transmissions of multiple fog nodes and is promising for distributed wireless communications environments. Nonetheless, to the best of our knowledge, the problem of task allocation and resource allocation in NOMA-enabled multipoint collaborative offloading in Vehicular Fog Computing (VFC) still remains open. With this consideration, the NOMA-enabled vehicular fog computing problem is investigated in this work, as well as an energy-efficient NOMA-enabled vehicular computing offloading scheme is proposed. The scheme combines task vehicles, main fog access points (F-APs), idle vehicles, and auxiliary F-APs to collaborate on tasks. However, the corresponding optimization problem turns out to be a non-convex issue. To this end, through in-depth mathematical analysis, the monotonicity of NOMA power allocation is discussed to find the optimal power allocation coefficient. Furthermore, an interior-point method based on successive convex approximation (SCA) is proposed to obtain the sub-optimal solution of task division and bandwidth allocation. Simulations are conducted to validate our analysis and corroborate the effectiveness of the proposed scheme.
Keyword ：
Cooperative computation offloading Cooperative computation offloading Energy consumption Energy consumption NOMA NOMA VFC VFC
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| GB/T 7714 | Lin, Zhijian , Lin, Yonghang , Yang, Jianjie et al. Energy-Efficient joint Resource Allocation and Computation Offloading in NOMA-enabled Vehicular Fog Computing [J]. | MOBILE NETWORKS & APPLICATIONS , 2024 . |
| MLA | Lin, Zhijian et al. "Energy-Efficient joint Resource Allocation and Computation Offloading in NOMA-enabled Vehicular Fog Computing" . | MOBILE NETWORKS & APPLICATIONS (2024) . |
| APA | Lin, Zhijian , Lin, Yonghang , Yang, Jianjie , Zhang, Qingsong . Energy-Efficient joint Resource Allocation and Computation Offloading in NOMA-enabled Vehicular Fog Computing . | MOBILE NETWORKS & APPLICATIONS , 2024 . |
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In this paper, we develop a non-coherent differential chaos shift keying based index modulation by using initial value index (IVI-DCSK) to convey additional information for wireless communications. In the proposed scheme, mc mapped bits are carried by 2(c)(m) chaotic sequences by exploiting the quasi-orthogonality of different chaotic signals, while the modulated bit is carried by DCSK. To diminish the multiuser interference, the references allocated to different users are sent in individual time slots, while the information-bearing sequences for the mapped bits of users are sent simultaneously. We then derive the bit error rate (BER) expression of multi-user IVI-DCSK over multipath Rayleigh fading channels. The theoretical and consistent simulation results show that the proposed IVI-DCSK achieves significant gains over the conventional chaotic-based index modulations, i.e., permutation index DCSK (PI-DCSK) and code index modulation DCSK (CIM-DCSK). This gain can be more than 4 dB in fading channels with high multipath delay. In addition, it achieves higher energy and spectral efficiencies over the latter ones. The superiority of the proposed scheme is further verified in practical ultra-wideband (UWB) communications. Thus, this proposed scheme is efficient and promising for chaotic-based low-complexity communications, such as in wireless local area network (WLAN) and indoor applications.
Keyword ：
Chaotic communication Chaotic communication Codes Codes differential chaos shift keying (DCSK) differential chaos shift keying (DCSK) Indexes Indexes index modulation (IM) index modulation (IM) Modulation Modulation multiple access (MA) multiple access (MA) Symbols Symbols Vectors Vectors Wireless communication Wireless communication
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| GB/T 7714 | Chen, Pingping , Chen, Haoyu , Shi, Long et al. Initial Chaotic Value-Based Index Modulation for Wireless Communications [J]. | IEEE TRANSACTIONS ON COMMUNICATIONS , 2024 , 72 (10) : 6014-6028 . |
| MLA | Chen, Pingping et al. "Initial Chaotic Value-Based Index Modulation for Wireless Communications" . | IEEE TRANSACTIONS ON COMMUNICATIONS 72 . 10 (2024) : 6014-6028 . |
| APA | Chen, Pingping , Chen, Haoyu , Shi, Long , Lin, Zhijian , Li, Yong . Initial Chaotic Value-Based Index Modulation for Wireless Communications . | IEEE TRANSACTIONS ON COMMUNICATIONS , 2024 , 72 (10) , 6014-6028 . |
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