Vehicular Communications最新文献

{"title":"Leveraging reputation for enhanced decision accuracy in vehicle-to-vehicle communications under limited infrastructure","authors":"Dimah Almani ,&nbsp;Tim Muller ,&nbsp;Steven Furnell","doi":"10.1016/j.vehcom.2025.100927","DOIUrl":"10.1016/j.vehcom.2025.100927","url":null,"abstract":"<div><div>Vehicle-to-Vehicle (V2V) networking enhances transportation safety and efficiency by enabling vehicles to share alerts. However, malicious vehicles may inject false messages, leading to disputes. While certificates help ensure security, Certificate Revocation List (CRLs) may be outdated in low-connectivity areas, making it hard to verify conflicting reports. Reputation systems, using a pre-signature scheme, can aid decision-making even in infrastructure-limited environments.</div><div>In this paper, we provide the mechanisms to use reputation in areas with low/no connectivity, whilst allowing for pseudonymous certificates to verify message authenticity without breaking privacy. The approach is integrated into the existing Security Credential Management System (SCMS), a framework for managing digital certificates for secure V2V communication.</div><div>Our simulations evaluate the security performance of our proposed mechanism, with offline available reputation, against plain SCMS certificate management that rely solely on CRL to block malicious vehicles. The results are achieved by integrating vehicular simulation tools like SUMO, OMNeT++, and Veins, to evaluate the V2V communications in each system under two conditions (Accident and No accident) ensuring a comprehensive system evaluation.</div><div>The proposed scheme improves accuracy in decision-making with conflicting information by 36% in accidents and 44.4% in No-Accident situations in a rural environment.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100927"},"PeriodicalIF":5.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870049","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":"Optimal coordinated platoon lane change in highways with mixed traffic","authors":"Fernando V. Monteiro ,&nbsp;Ketan Savla ,&nbsp;Petros Ioannou","doi":"10.1016/j.vehcom.2025.100924","DOIUrl":"10.1016/j.vehcom.2025.100924","url":null,"abstract":"<div><div>In the field of connected autonomous vehicles, platoons - where vehicles closely follow one another - have shown promising results in enhancing safety, traffic flow, and fuel efficiency. This study addresses the unique challenges of platoon lane changes, where multiple platoon vehicles have lane change intention and must remain together after the maneuver is completed. We focus on highway environments because many studies have highlighted the advantages of platooning in these settings. We leverage an offline controller synthesis approach to deal with the combinatorial problem of choosing a strategy. Building on concepts from symbolic optimal control, we represent the problem using a weighted directed acyclic graph where nodes are quantized state vectors, edge weights are costs to transition between nodes, and the shortest path solutions represent the optimal platoon lane change strategies. We use a Cached Branch-and-Bound Depth-First Search algorithm to solve the offline control problem due to its anytime capability and low memory requirements. This approach provides real-time decision making and guarantees maneuver success while minimizing completion time or control effort. Previous works either required control of all vehicles on the road, making them inadequate for mixed-traffic scenarios, or fixed the order in which platoon vehicles change lanes, disregarding the current state of surrounding vehicles and maneuver costs. Our framework can describe all previously proposed methods, relies only on cooperation between platoon vehicles, allows for optimization, and produces solutions whose costs decrease as the allowed computational time increases. We employ the VISSIM traffic simulator to compare our approach to the state of the art. The experiments show that we obtain an increase of 13% in the maneuver completion rate along with a decrease of around 15% to 20% in the maneuver completion time and distance traveled to complete the lane change at the cost of an average increase of 2% to 17% in the longitudinal control effort. This trade-off is a direct consequence of having the platoon occupy suitable lane-changing spaces as soon as possible, and this myopic behavior is necessary when there is no information about the future movements of human-driven vehicles. Moreover, the experiments indicate that our approach yields a sharp decrease in cost in relatively short computational times. These results emphasize the potential for deployment of the proposed method in mixed-traffic highway scenarios.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100924"},"PeriodicalIF":5.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870048","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 adaptive bendable virtual tunnel routing protocol for flying ad-hoc networks","authors":"Huizhi Tang ,&nbsp;Demin Li ,&nbsp;Yihong Zhang ,&nbsp;Xuemin Chen ,&nbsp;Abdul Rauf","doi":"10.1016/j.vehcom.2025.100922","DOIUrl":"10.1016/j.vehcom.2025.100922","url":null,"abstract":"<div><div>Flying ad-hoc networks (FANETs) play a crucial role in disaster response, surveillance, and remote sensing. However, their highly dynamic topology and frequent link disruptions pose significant challenges to efficient routing. Existing protocols suffer from excessive control overhead, unstable links, and inefficient energy utilization, that limits their practical deployment. To address these issues, we propose an adaptive bendable virtual tunnel routing protocol (ABVTR), which constructs a three-dimensional (3D) adaptive bendable virtual relay tunnel (3D-ABVRT) using Bézier curves. This tunnel restricts the propagation of route request messages, reducing redundant transmissions, and enhancing routing stability, particularly in sparsely connected UAV networks. ABVTR employs a piecewise function to align UAV movement with the tunnel's centerline, effectively minimizing deviations and reducing delays. Furthermore, it dynamically determines the next-hop node by considering movement direction, relative speed, and residual energy. The latter two factors are assessed using a S-function and an exponential function, respectively, to enhance link reliability and optimize energy distribution. This work advances the state-of-the-art by introducing a more adaptive, energy-efficient, and scalable routing solution for FANETs. The simulation results show that ABVTR significantly outperforms existing protocols (EARVRT, iPipe, HMGOC, CF-GPSR, FM-DT-GDR) in end-to-end delay, packet delivery ratio (PDR), and routing overhead. These enhancements position ABVTR as a highly promising solution for mission-critical FANETs application, enabling more resilient, scalable, and efficient aerial networks.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100922"},"PeriodicalIF":5.8,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859967","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":"Enhancing security and trust using efficient privacy-preserving authentication in vehicular edge computing networks","authors":"Anwar Ghani ,&nbsp;Saeed Ullah Jan ,&nbsp;Shehzad Ashraf Chaudhry ,&nbsp;Rashid Ahmad ,&nbsp;Ashok Kumar Das ,&nbsp;Do Hyeun Kim","doi":"10.1016/j.vehcom.2025.100921","DOIUrl":"10.1016/j.vehcom.2025.100921","url":null,"abstract":"<div><div>The Internet of Vehicles (IoV) requires advanced safety, security, and services in Intelligent Transportation Systems (ITS). Frequent broadcast message intervals and Dedicated Short-Range Communication (DSRC) make validating messages in such short timeframes extremely challenging. Additionally, current authentication protocols cannot meet the demands of the environment due to high communication and computational overheads. Furthermore, lightweight authentication proposals have been put forth to solve the problem; however, such attempts cannot provide a sophisticated solution that can handle advanced security needs and suffer from accuracy issues. This article presents a two-factor authentication protocol using lightweight cryptographic operations such as one-way hashing and exclusive OR (XOR) with acceptable efficiency and security. The identities are generated using Physically Unclonable Functions (PUFs), passwords, and randomized nonces to ensure two-factor authentication. The proposal is rigorously verified through formal security analysis, confirming that the protocol is untraceable, anonymous, protects key secrecy, and is resistant to well-known attacks in the IoV domain. The performance analysis confirms its robustness and reliability, with 43.31% low energy consumption in terms of computation, communication, and support for more security requirements, making it a feasible solution for the IoV domain.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100921"},"PeriodicalIF":5.8,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855879","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":"Maximizing the energy efficiency using M-PSO in multi-hop UAV-IRS network for improved post-disaster emergency communication services","authors":"Humairah Hamid,&nbsp;G.R. Begh","doi":"10.1016/j.vehcom.2025.100920","DOIUrl":"10.1016/j.vehcom.2025.100920","url":null,"abstract":"<div><div>Natural disasters often damage the ground infrastructure, leading to communication failures that hamper emergency response efforts. Solutions dependent on ground-based infrastructure suffer from severe limitations in these scenarios owing to fixed positions, limited energy sources, and limited coverage. Existing methodologies, often relying on terrestrial relay points or fixed infrastructure, face challenges in adjusting to rapidly changing conditions in disaster areas, leading to ineffective energy consumption and limited communication range. To address this challenge, this work proposes a novel approach that employs Unmanned Aerial Vehicles (UAVs) alongside Intelligent Reflecting Surface (IRS) to deal with the connectivity challenges and provide energy-efficient communication services for Ground Users (GUs). The proposed framework includes a multi-hop communication model in which UAV-IRS units function as mobile relays, establishing strong connections between the affected area nodes and a temporary base station. We propose a Modified Particle Swarm Optimization (M-PSO) technique that optimally adjusts UAV placement and transmit power while the IRS phase shifts are independently optimized using Gradient Descent (GD) to enhance energy efficiency. Simulation results indicate that our setup significantly enhances communication capabilities in a disaster-stricken region, outperforming conventional methods for enhancing coverage and energy efficiency, thereby providing a resilient alternative for emergency communication in disaster-affected regions.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"53 ","pages":"Article 100920"},"PeriodicalIF":5.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828420","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":"Joint carrier frequency offset, doubly selective channel estimation and data detection for RIS assisted MIMO OFDMA uplink system","authors":"A.G. Murali Krishna ,&nbsp;P.S. Sanoopkumar ,&nbsp;S.M. Sameer","doi":"10.1016/j.vehcom.2025.100916","DOIUrl":"10.1016/j.vehcom.2025.100916","url":null,"abstract":"<div><div>With the presence of an array of passive elements embedded in a reconfigurable intelligent surface (RIS), estimation of time-varying channels between a fast-moving user and the fixed base station (BS) is more challenging than conventional static channels. In this paper, we propose a joint technique for the estimation of carrier frequency offset (CFO) and doubly selective channel (DSC), and data detection in the RIS-assisted multiple input multiple output (MIMO) orthogonal frequency division multiple access (OFDMA) uplink system. The time variations of the channel within the OFDMA symbol are represented using the basis expansion model (BEM), significantly reducing the number of estimated parameters. An autoregressive (AR) model is used to characterize the variations in BEM coefficients and CFOs over successive OFDMA symbols. A novel technique of combining the Schmidt extended Kalman filtering (SEKF) and Gaussian particle filtering (GPF) integrated with an iterative detector and decoder (IDD) receiver structure (IDD-SKGPF) is proposed to estimate the BEM coefficients, CFOs and to detect the symbols in two stages. Performance of the proposed method is evaluated using normalized mean square error (NMSE) and compared with the derived Bayesian Cramer-Rao bound (BCRB) and modified BCRB. Furthermore, the reflection coefficient is optimized in the time domain by maximizing the achievable rate to demonstrate that the exploitation of RIS may result in significant bit error rate (BER) performance improvement of <span><math><mn>6</mn><mi>d</mi><mi>B</mi></math></span> in SNR over non optimized RIS scenario even under high mobility scenarios.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"53 ","pages":"Article 100916"},"PeriodicalIF":5.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828418","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":"Task offloading and computational scheduling in RIS-assisted low Earth orbit satellite communication networks","authors":"Yin Wang,&nbsp;Kang'An Gui","doi":"10.1016/j.vehcom.2025.100917","DOIUrl":"10.1016/j.vehcom.2025.100917","url":null,"abstract":"<div><div>This article investigates the joint optimization of task offloading and computation scheduling in low Earth orbit (LEO) satellite networks, where each LEO satellite is equipped with a reconfigurable intelligent surface (RIS). By considering the inherent characteristics of tasks and the energy consumption associated with task execution, we define a system utility function and formulate the problem as a constrained utility maximization problem. To address this optimization challenge, we first propose a priority-based task offloading and computation scheduling strategy tailored for single-satellite execution scenarios. Subsequently, we extend this approach to multi-satellite collaborative task execution scenarios, where a knapsack algorithm-based strategy is developed to optimize task allocation and scheduling. To underscore the advantages of the proposed RIS-assisted multi-satellite framework, we introduce a comparative analysis with a non-RIS-assisted multi-satellite offloading mode. Extensive simulations conducted in Satellite Tool Kit (STK) and MATLAB demonstrate that the RIS-assisted multi-satellite mode significantly outperforms its non-RIS counterpart in terms of system utility and energy efficiency. The results validate the effectiveness of the proposed algorithms and highlight the potential of RIS technology in enhancing the performance of LEO satellite networks.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"53 ","pages":"Article 100917"},"PeriodicalIF":5.8,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828419","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":"Privacy-aware revocation in VANETs with a Blockchain using accumulator","authors":"Jamile Khalili Shahrouz,&nbsp;Morteza Analoui","doi":"10.1016/j.vehcom.2025.100918","DOIUrl":"10.1016/j.vehcom.2025.100918","url":null,"abstract":"<div><div>In recent years, Vehicular Ad-hoc Networks (VANETs) have gained widespread acceptance to enable vehicles to communicate and exchange critical information, such as road conditions, traffic congestion, speed, and vehicle locations. Nonetheless, the wireless nature of VANET communication renders it susceptible to various security attacks. To counter these vulnerabilities, privacy-preserving authentication schemes play a crucial role. Many of these schemes rely on Public Key Infrastructure (PKI) to mitigate security risks, ensuring authentication and message integrity through public key certificates. However, a significant drawback of these schemes arises from utilizing the Certificate Revocation List (CRL), which introduces notable delays. In addition, vehicular networks are time-sensitive, and prolonged delays may lead to severe consequences. Moreover, CRL checking can inadvertently leak sensitive vehicle information, making PKI-based schemes impractical for VANETs. To address these challenges, we propose a privacy-preserving revocation mechanism based on a zero-knowledge accumulator, tailored specifically for VANETs. This mechanism significantly reduces the time spent checking revoked certificates while preserving user privacy. Furthermore, by utilizing Blockchain technology to publish revoked certificates in a distributed manner, we can reduce the time required for distribution, decrease network congestion, improve efficiency, and eliminate reliance on a single central authority. Additionally, our approach aims to overcome the issue of non-membership witness updates in batch mode. Our proposed privacy-aware scheme has been rigorously evaluated using the automatic verification tool ProVerif. The results confirm that our solution guarantees the desired properties of anonymity and unlinkability. Through extensive simulation and performance analysis, we demonstrate that our scheme is not only privacy-preserving but also an efficient and practical solution for real-world deployment in VANETs.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"53 ","pages":"Article 100918"},"PeriodicalIF":5.8,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828366","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 distributed multi-agent joint optimization algorithm based on CERL and A2C for resource allocation in vehicular networks","authors":"Ming Sun ,&nbsp;Zexu Jiang ,&nbsp;Erhan Dong ,&nbsp;Tianyu Lv","doi":"10.1016/j.vehcom.2025.100919","DOIUrl":"10.1016/j.vehcom.2025.100919","url":null,"abstract":"<div><div>Vehicular networking plays an indispensable role in enhancing road safety and traffic efficiency. Although existing technologies have made significant progress in reusing vehicle-to-infrastructure (V2I) link resources for vehicle-to-vehicle (V2V) links, they still face challenges such as the high dimensionality of the joint action space and unsatisfactory optimization with limited in-vehicle radio resources, variable environments, and uncertainties. Reinforcement learning-based joint algorithms that separately optimize channel allocation and power selection can reduce the dimensionality of the joint action space. However, it is difficult to effectively coordinate channel allocation and power selection, which greatly affects the performance of them. To address these challenges, this paper proposes a distributed multi-agent joint optimization algorithm based on a novel cross-entropy loss-based reinforcement learning (CERL) algorithm and the A2C algorithm for separately optimizing channels and power in vehicular networks. Furthermore, a multi-round stochastic search strategy is presented to optimize the experience pools and coordinate the channel allocation and the power selection for the proposed distributed multi-agent joint optimization algorithm. With the help of the multi-round stochastic search strategy, the proposed distributed multi-agent joint optimization algorithm can significantly improve the optimization performance in resource allocation. To evaluate the performance of the proposed distributed multi-agent joint optimization algorithm in both the V2V link transmission success rate and the V2I link throughput, a comprehensive simulation study is conducted under different channel resource availability scenarios with different sizes of security data. The experimental results demonstrate that our proposed algorithm can significantly improve the V2I link throughput and the V2V link transmission success rate, and outperforms the existing algorithms in terms of radio efficiency. Specifically, under two different channel resource availability scenarios, our proposed algorithm can achieve more than 99.9 % average V2V link transmission success rate and 2.99 Mbps and 2.07 Mbps higher average V2I link throughput than the competitive algorithm D3QN-LS when the security data size ranges from 1 × 1060 Bytes to 8 × 1060 Bytes. The proposed algorithm theoretically provides a new perspective and solution for separately optimizing channels and power in high-dimensional complex dynamic environments of vehicular networks.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"53 ","pages":"Article 100919"},"PeriodicalIF":5.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825647","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":"QRCF: A new Q-learning-based routing approach using a smart cylindrical filtering system in flying ad hoc networks","authors":"Amir Masoud Rahmani ,&nbsp;Amir Haider ,&nbsp;Monji Mohamed Zaidi ,&nbsp;Abed Alanazi ,&nbsp;Shtwai Alsubai ,&nbsp;Abdullah Alqahtani ,&nbsp;Mohammad Sadegh Yousefpoor ,&nbsp;Efat Yousefpoor ,&nbsp;Mehdi Hosseinzadeh","doi":"10.1016/j.vehcom.2025.100905","DOIUrl":"10.1016/j.vehcom.2025.100905","url":null,"abstract":"<div><div>To ensure reliable data transmission in flying ad hoc networks (FANETs), efficient routing protocols are necessary to establish communication paths in FANETs. Recently, reinforcement learning (RL), particularly Q-learning, has become a promising approach for overcoming challenges faced by traditional routing protocols due to its capacity for autonomous adaptation and self-learning. This study presents a Q-learning-based routing strategy, enhanced by an innovative cylindrical filtering technique, named QRCF in FANETs. In QRCF, the dissemination interval of hello packets is adaptively adjusted based on the connection status of nearby UAVs. Then, this routing process leverages Q-learning to discover reliable and stable routes, using a state set refined by the cylindrical filtering technique to accelerate the search for the optimal path in the network. Afterward, the reward value is computed using metrics such as relative speed, connection time, residual energy, and movement path. Finally, QRCF is deployed in the network simulator 2 (NS2), and its performance is evaluated against three routing schemes, QRF, QFAN, and QTAR. These evaluations are presented based on the number of UAVs and their speed. In general, when changing the number of nodes, QRCF improves energy usage (about 5.01%), data delivery ratio (approximately 1.20%), delay (17.71%), and network longevity (about 3.21%). However, it has a higher overhead (approximately 10.91%) than QRF. Moreover, when changing the speed of UAVs in the network, QRCF improves energy usage (about 4.94%), data delivery ratio (approximately 2.36%), delay (about 17.5%), and network lifetime (approximately 8.75%). However, it increases routing overhead (approximately 15.47%) in comparison with QRF.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"53 ","pages":"Article 100905"},"PeriodicalIF":5.8,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792512","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}