Vehicular Communications最新文献

{"title":"A Multi-Head Attention mechanism assisted MADDPG algorithm for real-time data collection in Internet of Drones","authors":"A.K.M. Atiqur Rahman ,&nbsp;Muntasir Chowdhury Mridul ,&nbsp;Palash Roy ,&nbsp;Md. Abdur Razzaque ,&nbsp;Md. Rajin Saleh ,&nbsp;Mohammad Mehedi Hassan ,&nbsp;Md Zia Uddin","doi":"10.1016/j.vehcom.2025.100944","DOIUrl":"10.1016/j.vehcom.2025.100944","url":null,"abstract":"<div><div>Flexible movement and rapid deployment capabilities of unmanned aerial vehicles (UAVs) or drones have enabled them to be ideal for fresh and real-time data collection in the Internet of Drones (IoD) network. With the rising demand for IoD applications, optimizing the Age of Information (AoI), and energy efficiency of drones has become a challenging problem. The existing literature works are either limited by considering single-drone data collection from 2D space or by not prioritizing data from diverse IoT devices. In this paper, we have developed an optimization framework for multi-drone-assisted data collection in 3D space, which brings a trade-off between minimizing drone energy consumption and AoI, exploiting the Mixed Integer Linear Programming (MILP) problem. However, due to the NP-hardness of the developed optimization framework for large networks, we have devised a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, supported and enhanced by a Multi-Head Attention (MHA) mechanism for multi-drone-assisted data collection to minimize drone energy consumption and AoI jointly, namely MECAO. The MHA in the MECAO system helps prioritize IoT data sources and ensures the timely collection of important data. This system enables the agents to coordinate effectively among themselves and provides innovative solutions to complex network issues. Our findings demonstrate substantial advancements in real-time data collection and drone performance, offering a practical and efficient solution for modern IoD applications. The developed MECAO system is implemented in the OpenAI Gym simulator platform, and the simulation trace file content depicts the improvement in AoI by up to 56% while the energy consumption is reduced by as high as 38.5%, respectively, compared to the state-of-the-art works.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100944"},"PeriodicalIF":5.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive UAV-assisted secure and reliable communications based on robust joint trajectory and power control optimization","authors":"Can Wang,&nbsp;Junhong Zhang,&nbsp;Helin Yang","doi":"10.1016/j.vehcom.2025.100941","DOIUrl":"10.1016/j.vehcom.2025.100941","url":null,"abstract":"<div><div>The cognitive unmanned aerial vehicle (UAV) communication system has emerged as a pivotal technology in addressing the scarcity of spectral resources for UAV communications, but the jamming and eavesdropping attacks are severe due to the high-quality air-to-ground communication links. Consequently, this paper introduces a UAV-enabled cooperative jammer to disrupt the eavesdropping activities of active eavesdroppers by emitting artificial noise. Our objective is to jointly optimize the three-dimensional UAV trajectory and transmit power to maximize the secrecy communication rate under quality of service (QoS) requirement. To tackle the non-convex problem, the block coordinate descent (BCD) and successive convex approximation (SCA) methods are utilized to transform it into an approximate convex problem, and then we design an alternative optimization iterative algorithm to achieve suboptimal but efficient solution. Moreover, we extend the developed algorithm into an imperfect channel state information (CSI) scenario to maximize the worst-case secrecy rate by jointly optimizing the robust UAV's trajectory and transmit power, where the location uncertainties of ground primary, secondary, and eavesdropping devices are considered. Simulation results demonstrate that the proposed joint optimization algorithm significantly enhances system secrecy performance under different real-world settings compared to existing state-of-the-art algorithms.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100941"},"PeriodicalIF":5.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Millimeter-wave vehicular collaborative communication assisted by intelligent reflecting surface","authors":"Xiangrui Guan,&nbsp;Jianbin Xue,&nbsp;Han Zhang,&nbsp;Jialing Xu","doi":"10.1016/j.vehcom.2025.100940","DOIUrl":"10.1016/j.vehcom.2025.100940","url":null,"abstract":"<div><div>The combination of the intelligent reflecting surface (IRS) with reconfigurable wireless propagation environment and the millimeter-wave (mmWave) with abundant bandwidth resources can play a great advantage over the rate and delay in vehicular communications. Considering the problem of non-line-of-sight (NLOS) communication between the requesting nodes (RNs) and the service nodes (SNs) in the mmWave vehicular system in this paper, we propose an IRS-assisted multi-hop vehicle-to-vehicle (V2V) cooperative communication method to realize low-delay vehicular communication. Aiming to minimize the communication delay of RNs, an optimization problem is formulated by optimizing the link selection and reflection coefficient matrix of IRS. To tackle the optimization problem, an alternate optimization algorithm is proposed to decompose the original optimization problem into two subproblems for iterative optimization. First, we establish a link selection mechanism based on link quality and vehicle distance and propose a link selection algorithm based on the evaluation function to select communication links for each RN. Then, in particular, we derive the closed-form expression based on successive convex approximation (SCA) techniques for updating the reflection coefficient matrix of IRS. The simulation results show that the IRS-assisted mmWave vehicular cooperative communication scheme proposed in this paper can effectively reduce the communication delay and improve the performance of the mmWave vehicular network.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100940"},"PeriodicalIF":5.8,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CLE-based authenticated key agreement with PUF-secured key for vehicle-to-infrastructure","authors":"Suhui Liu ,&nbsp;Liquan Chen ,&nbsp;Liqun Chen ,&nbsp;Yu Wang ,&nbsp;Yaqing Zhu","doi":"10.1016/j.vehcom.2025.100942","DOIUrl":"10.1016/j.vehcom.2025.100942","url":null,"abstract":"<div><div>Vehicle-to-infrastructure (V2I) communication is the basis for vehicles to obtain information about the road ahead. The confidentiality and reliability of V2I communication guarantee traffic safety and smooth flow. Authenticated key agreement (AKA) is the most commonly used technique to establish secure communication channels. Signature-based AKA inevitably exposes the identity information of vehicles, while Encryption-based AKA can bring deniability and high privacy, which means no adversary can know who sent the AKA message. Certificateless encryption (CLE) can simultaneously solve burdensome certificate management and key escrow. However, existing certificateless cryptography requires two loosely combined public keys to represent a device and does not consider the physical security of storing secret keys locally. This paper first designed an improved CLE scheme with one-device-one-public-key, and performance comparisons show that the proposed CLE has optimal storage and computation performance. Considering that rare work was put on encryption-based AKA, this paper proposed a deniable and privacy-preserving certificateless AKA for V2I communication by incorporating Physically Unclonable Function (PUF)-secured key management to prevent physical leakage of keys, named CLE-AKA-PUF. Feature comparison illustrates that CLE-AKA-PUF supports key escrow-free, dual authentication, physical security, deniability, and high privacy. Security proofs and performance analysis demonstrate the practicability and efficiency of CLE-AKA-PUF.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100942"},"PeriodicalIF":5.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perceptual data importance and freshness aware transmission in millimeter wave vehicular networks","authors":"Chenyuan He ,&nbsp;Zhouyu Zhang ,&nbsp;Yingfeng Cai ,&nbsp;Hai Wang ,&nbsp;Long Chen ,&nbsp;Fenghua Huang","doi":"10.1016/j.vehcom.2025.100939","DOIUrl":"10.1016/j.vehcom.2025.100939","url":null,"abstract":"<div><div>The extensive sharing of perceptual data between vehicles and between vehicles and roads has significantly enhanced the performance of intelligent transportation system (ITS). The current vehicular networks using sub-6 GHz struggle to meet the demands for high-rate, low-latency, and highly reliable communication. To address this issue, this paper proposes a perceptual data sharing strategy based on millimeter-wave (mmWave) communication technology. This strategy takes into account the characteristics of vehicular perceptual data, i.e., the importance and freshness of the data, and constructs a mixed-integer nonlinear sum-of-ratios optimization problem. To meet the stringent real-time decision-making requirements of vehicular networks, we leverage the transmission slot characteristics of the Time Division Multiple Access (TDMA) Medium Access Control (MAC) architecture to transform the nonlinear original problem into a series of approximate integer linear programming (ILP) problems. Then we employ maximum weight matching in graph theory to further reduce computational complexity, enabling the problem to be solved in polynomial time. Additionally, we have designed a brute-force algorithm to ensure the global optimum is achieved, thereby validating the performance of our proposed algorithm. Comparative simulation studies with the brute-force algorithm, the ILP solver, the edge coloring algorithm, our previously developed parameterization-based iterative algorithm (PIA), and the First-Come-First-Serve (FCFS) scheduling scheme verify the effectiveness of our proposed algorithm.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100939"},"PeriodicalIF":5.8,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A privacy-preserving access control protocol for 6G supported intelligent UAV networks","authors":"Khalid Mahmood ,&nbsp;Salman Shamshad ,&nbsp;Mohammad Hossein Anisi ,&nbsp;Alessandro Brighente ,&nbsp;Muhammad Asad Saleem ,&nbsp;Ashok Kumar Das","doi":"10.1016/j.vehcom.2025.100937","DOIUrl":"10.1016/j.vehcom.2025.100937","url":null,"abstract":"<div><div>Due to their autonomous operation, high mobility, and real-time communication capabilities, 6G-supported Unmanned Aerial Vehicles (6G-UAVs) (i.e., drones) are increasingly being utilized to enhance data collection and management in Intelligent Transportation Systems (ITSs). Despite their manifold benefits, 6G-supported UAV-based ITS (6G-U-ITS) faces unique security challenges beyond conventional cyber and physical threats. These include real-time authentication, impersonation attacks, physical tampering or cloning and protection against identity spoofing in highly dynamic environments. For instance, an attacker may steal a drone and use its identity to send authenticated malicious messages to the ITS, causing road accidents. Therefore, a secure authentication scheme must ensure resilience against UAV identity theft and unauthorized access while maintaining low-latency and computational efficiency to support the stringent real-time security requirements of 6G-U-ITS. Existing authentication schemes are not specifically designed to address these challenges, making it imperative to develop a lightweight and robust authentication mechanism tailored for 6G-U-ITS. Moreover, most of the existing protocols are vulnerable to physical tampering and impersonation attacks and also require high computation overhead. In this paper, to mitigate these limitations and satisfy the aforementioned requirements, we propose a secure access control protocol for 6G-U-ITS. To the best of our knowledge, this is the first security solution in the literature that can achieve security against UAVs physical attacks. Furthermore, we justify the robustness of the designed protocol against potential attacks through detailed formal and informal security assessment. Via testbed experiments, we show that our protocol achieves 20.66% and 22.82% higher efficiency on communication and computation overhead, respectively, compared to other contemporary competing protocols.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100937"},"PeriodicalIF":5.8,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EGBCR-FANET: Enhanced genghis Khan shark optimizer based Bayesian-driven clustered routing model for FANETs","authors":"Reham R. Mostafa ,&nbsp;Dilna Vijayan ,&nbsp;Ahmed M. Khedr","doi":"10.1016/j.vehcom.2025.100935","DOIUrl":"10.1016/j.vehcom.2025.100935","url":null,"abstract":"<div><div>Unmanned Aerial Vehicle (UAV) technology has advanced rapidly, with broad use in both the military and commercial sectors. As a result, multi-UAV networks, also known as Flying Ad Hoc Networks (FANETs), have become a vital part of current communication systems. However, FANETs confront numerous challenges such as limited energy resources, high mobility, frequent topological changes, and inconsistent communication links. These difficulties influence network stability, limit data transmission efficiency, and shorten network longevity. Addressing these issues requires an adaptable routing strategy in FANETs. Cluster-based routing in UAVs is a great way to save energy, increase scalability, and improve network performance. This paper introduces a new clustering and routing framework for FANETs based on the Enhanced Genghis Khan Shark Optimizer (EGKSO). Unlike previous clustering approaches, the suggested solution dynamically selects the appropriate number of clusters while taking node coverage and network bandwidth into account. EGKSO is used to choose energy-efficient and stable cluster heads, resulting in balanced load distribution and a longer network lifetime. A dynamic cluster maintenance technique is proposed to ensure network stability and maintain efficient communication performance. In addition, a Bayesian-inspired next-hop selection model for adaptive routing is presented, allowing probabilistic decision-making to respond to network changes efficiently. This combination of swarm intelligence and probabilistic modeling improves communication reliability, reduces latency, and maximizes energy efficiency. The simulation results show that the suggested method outperforms existing clustering and routing protocols in terms of delivery ratio, energy consumption, latency, and clustering stability. The results demonstrate the efficacy of combining metaheuristic-based clustering with Bayesian-inspired routing, providing a resilient and scalable solution for FANETs in dynamic and resource-constrained contexts.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100935"},"PeriodicalIF":5.8,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geometric Optimisation of Unmanned Aerial Vehicle Trajectories in Uncertain Environments","authors":"J Akshya ,&nbsp;M Sundarrajan ,&nbsp;S. Amutha ,&nbsp;Rajesh Kumar Dhanaraj ,&nbsp;Adil O. Khadidos ,&nbsp;Alaa O. Khadidos ,&nbsp;Shitharth Selvarajan","doi":"10.1016/j.vehcom.2025.100938","DOIUrl":"10.1016/j.vehcom.2025.100938","url":null,"abstract":"<div><div>The problem of efficient trajectory optimisation for Unmanned Aerial Vehicles (UAVS) in dynamic and constrained environments is one where energy efficiency, spatial coverage, and path smoothness need to be balanced. The existing methods, namely RRT*, A*, and Dijkstra, are popular but generally heuristic and do not provide globally optimal solutions. They face significant limitations while dealing with complex geometries, dynamic obstacles, and multi-objective requirements. These challenges call for a mathematically sound framework that seamlessly integrates convex analysis and computational geometry to provide an optimal trajectory planning framework. This research work introduces a convex optimisation framework for UAV trajectory planning which unifies multiple objectives, like minimising energy consumption, maximising spatial coverage, and ensuring the smoothness of the path, into a single convex objective function. More importantly, it indicates that obstacle dynamics and uncertain environmental conditions are handled better by it, so it is relatively easier for safe and efficient navigation. Proven to converge faster and with higher precision than RRT*, A*, and Dijkstra, the approach proposed here enjoys intrinsic convex properties, which ensure global optimality. Qualitative measurements show the efficiency of the proposed framework. The result is energy efficiency of 90%, with 92% coverage, 98% constraint satisfaction, and 95% path smoothness, which is 15-25% better on all metrics than traditional approaches can offer. By bridging between theory in convex optimisation and practice for solving multi-objective problems in a dynamic setting, this study provides a more robust solution for UAV trajectory planning.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100938"},"PeriodicalIF":5.8,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rigid communication topologies: Impact on stability, safety, energy consumption, passenger comfort, and robustness of vehicular platoons","authors":"Amir Zakerimanesh ,&nbsp;Tony Zhijun Qiu ,&nbsp;Mahdi Tavakoli","doi":"10.1016/j.vehcom.2025.100936","DOIUrl":"10.1016/j.vehcom.2025.100936","url":null,"abstract":"<div><div>This paper investigates the impact of rigid communication topologies (RCTs) on the performance of vehicular platoons, aiming to identify beneficial features in RCTs that enhance vehicles behavior. Four performance metrics are introduced, focusing on safety, energy consumption, passenger comfort, and robustness of vehicular platoons. The safety metric is based on momentary distances between neighboring vehicles, their relative velocities, and relative accelerations. Thus, to have access to these relative values, the coupled dynamics between pairs of neighboring vehicles are formulated, considering initial conditions (position, velocity, acceleration), the velocity/acceleration trajectory of the leader vehicle, deployed RCT, and the parity/disparity between vehicles. By decoupling the dynamics using a mapping matrix structured on deployed RCT, the features of the vehicles, and control gains, precise formulations for distance errors, relative velocities, and relative accelerations between all neighboring vehicles, over the travel time, are obtained. Comparing performance metric results across RCTs highlights that downstream information transmission—from vehicles ahead, particularly the leader vehicle, to vehicles behind—significantly enhances platoon stability, safety, energy consumption, and passenger comfort metrics. Conversely, receiving state information from vehicles behind degrades metrics, compromising safety, increasing energy consumption, and reducing passenger comfort. These findings underscore that forward-looking, leader-centric communications between vehicles markedly enhance platoon efficiency and safety.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100936"},"PeriodicalIF":5.8,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An optimal transmit power allocation scheme using UAV position estimation in MmWave NTNs","authors":"Pawan Srivastava,&nbsp;M.P.R.S. Kiran","doi":"10.1016/j.vehcom.2025.100934","DOIUrl":"10.1016/j.vehcom.2025.100934","url":null,"abstract":"<div><div>Non-terrestrial networks (NTNs) typically consist of UAV swarms equipped with multiple sensors that generate massive data, requiring real-time communication to a gateway for further processing. Hence, millimeter-wave (mmWave) communication technologies operating above 24 GHz emerge as a suitable solution for enabling high-speed intra-UAV swarm communication. However, mmWave communication technologies use multiple antenna-based directional beamforming for improved coverage, which leads to higher power consumption and frequent beam training overhead, affecting swarm endurance. To address this, we propose a novel optimal transmit power allocation scheme that enhances swarm endurance and improves throughput by reducing beam training overhead. Firstly, the proposed scheme uses the Kalman filter (in this paper, but not limited to) at the transmitting UAV to estimate the real-time position of the receiving UAV. The estimated position is utilized to calculate path loss and select the optimal transmit power level needed to meet the required received signal power threshold at the receiving UAV. To reduce outages from errors in UAV position estimation, the proposed scheme also adjusts the transmit power level by incorporating an additional buffer distance around the estimated position, thereby enhancing reliability with a minimal increase in transmit power. The performance analysis shows that the proposed scheme achieves an average reliability of more than 99% and power savings of up to 49.4% while increasing the throughput under saturated traffic conditions, thus establishing its effectiveness in mobile UAV swarms. Also, the proposed scheme is compared with three popular mechanisms existing in the literature: 1) baseline approach where constant transmit power is utilized, 2) deep learning (long short-term memory, LSTM) based transmit power allocation, and 3) power allocation using <span><math><mi>α</mi><mo>−</mo><mi>β</mi><mo>−</mo><mi>γ</mi></math></span> filter for receiving UAV position estimation. The performance comparison shows that the proposed scheme offers superior performance in terms of power savings, reliability, throughput, and computational complexity.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100934"},"PeriodicalIF":5.8,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}