International Journal of Vehicle Information and Communication Systems (8 papers in press)

Regular Issues

• Efficient clustering for wireless sensor networks using modified bacterial foraging algorithm  
  by Dharmraj Biradar, Dharmpal D. Doye, Kulbhushan A. Choure 
  Abstract: The energy efficiency and clustering are directly related to each other in Wireless Sensor Networks (WSNs). A significant number of methods have been introduced for energy-efficient clustering in the last couple of decades. To limit energy use and improve network throughput, various methods for the clustering algorithm were introduced using an optimisation algorithm, fuzzy logic, and thresholding techniques. The optimisation algorithms such as Particle Swarm Optimisation (PSO), Genetic Algorithm (GA), Ant Colony Optimisation (ACO) and their variants were presented, but the challenge of selecting the efficient Cluster Head (CH) and cluster formation around it with minimum overhead and energy consumption is unresolved. In this paper, energy proficient and lightweight clustering algorithm for WSNs is proposed using the Modified Bacterial Foraging optimisation Algorithm (MBFA). The aim of designing the MBFA is to limit energy use, control overhead, and improve network throughput in this paper. The process of CH selection using MBFA is performed via a novel fitness function. The wellness capacity is planned using key parameters, for example, remaining energy, node degree, and geographical distance between sensors to base station. The MBFA selects the sensor node as CH using the fitness value. The proposed clustering protocol is simulated and evaluated with state-of-art protocols to justify efficiency.
  Keywords: bacterial foraging optimisation; clustering; cluster head selection; energy efficiency; particle swarm optimisation.
  
  
• Efficient resource allocation scheme using PSO-based scheme of D2D communications for overlay networks  
  by Yogesh Kumar Sharma, Bharat Ghanta, Pavan Mishra, Shailesh Tiwari 
  Abstract: Device-to-Device communication (D2D) is an essential technology in cellular networks which enables direct communication between devices and supports the high data rate compared with cellular communication. To improve the system capacity, multiple D2D uses are allowed to share the same resource block. With the limited number of available resource blocks, it is very challenging to assign a resource block for newly formed D2D pairs. Furthermore, to solve the aforementioned problem, an effective resource allocation scheme is proposed that gives the minimum number of required resource blocks for a given link. The proposed scheme is based on particle swarm optimisation (PSO). The proposed scheme reduces the number of resource blocks for a given D2D link and improves the network throughput. Moreover, compared with greedy and LIFA schemes, the proposed scheme could set aside to 26.69% resource blocks around and enhance the throughput per resource block by up to 34.4%.
  Keywords: device-to-device communication; interference; overlay network; PSO; resource block.
  
  
• Blockchain-based secure authentication protocol for vehicular ad-hoc networks  
  by Ram Baksh, Samiulla Itoo, Musheer Ahmad 
  Abstract: Vehicular Ad Hoc Networks (VANETs) facilitate communication among vehicles and roadside units (RSUs) to enhance road safety and traffic efficiency. However, ensuring the security and privacy of communications in VANETs remains a significant challenge. In this paper, we propose a Blockchain-based Conditional Privacy-Preserving Authentication (BCPPA) protocol for VANETs to address these challenges. The protocol leverages Blockchain technology for secure data storage and employs smart contracts for authentication and revocation processes. Furthermore, we introduce a key derivation algorithm to alleviate the burden of key pre- storing in vehicle On-Board Units (OBUs). Our protocol utilizes modified Elliptic Curve Digital Signature Algorithm (ECDSA) with batch verification to enhance verification efficiency in VANETs. We provide a detailed description of the protocol, along with security and performance analysis, demonstrating its effectiveness in ensuring secure and privacy-preserving communications in VANETs.
  Keywords: blockchain; ROR model; elliptic curve cryptography; smart contract; vehicular ad-hoc network.
  DOI: 10.1504/IJVICS.2025.10074924
   
  
• Societal impact of resource management in vehicular communication networks  
  by Vartika Agarwal, Gagan Bansal, Sachin Sharma 
  Abstract: Evaluating and trusting communication between vehicles is crucial to developing intelligent Transportation Systems (ITS) and resource management in Vehicular Communication Networks (VCNs) is a central task to attain this aim. This article proposes an end-to-end method for resource management in VCNs, which includes radio resource allocation, network resource optimisation, forecasting methods and reinforcement learning techniques to advance system intelligence and efficiency. A real-world scenario case study is examined along the DelhiMathura corridor, where the techniques proposed are implemented to simulate and analyse resource behaviour in dynamic traffic scenarios. The work also examines resource sharing between multiple mobile virtual VCN operators, focusing on interoperator collaboration and fairness of resource allocation. The social benefit of effective resource management is also discussed, presenting advantages like fewer traffic jams, increased safety and better quality of service. This research acts as a point of reference for scholars and experts looking to create scalable and socially conscious VCN solutions.
  Keywords: VCN; vehicular communication network; PPO; proximal policy optimisation; RRM; radio resource management; V2V; vehicle-to-vehicle communication V2I; vehicle-to-infrastructure; ITS; intelligent transportation system; RL; reinforcement learning; NRM; network resource management.
  DOI: 10.1504/IJVICS.2025.10076195
   
  
• Parasitic element-based quasi-Yagi antenna for vehicular communication  
  by G. Indumathi, V. Guruatchaya 
  Abstract: A printed quasi-Yagi antenna using parasitic elements is proposed for automotive communication at 2.4 GHz. The design includes a driven element (such as a dipole or microstrip line) along with directors, which help focus the radiation pattern and improve signal directionality. By adding parasitic components like directors and reflectors, the antenna can more effectively focus its energy in one direction, improve gain and directivity without appreciably expanding its total size. Novelty of this work: Placing an antenna over vehicle and obtain increased gain, the signal strength in a specific direction becomes stronger. A Rogers/RT Duroid 5880 substrate with a thickness of 1.575 mm and a dielectric constant of 2.2 is used in the design. It was chosen based on its characteristics. The antenna is appropriate for portable devices and vehicle communication systems due to its small size (33 mm
  Keywords: V2V communication; quasi-Yagi antenna; parasitic elements; radiating elements.
  DOI: 10.1504/IJVICS.2026.10078496
   
  
• Enhanced FANET authentication model utilising lightweight key management and advanced elliptic curve cryptography for batch authentication  
  by Kusum Dalal 
  Abstract: The progress in avionics has driven the transformation of UAVs, elevating their functionalities and effectiveness. FANET, a subset of MANET, integrates UAVs into its network infrastructure, enabling seamless communication and coordination among them. Drones, commonly referred to as UAVs, are increasingly being deployed for the real-time acquisition of sensitive data. This underscores the critical importance of safeguarding the security and privacy of such data. To tackle this, a novel ECC-based FANET Authentication Protocol (EFAP) is proposed in this work. At first, the system is initialized and the registration process of end user and drones are done. Further, the mutual authentication is performed that utilizes the session key exchange protocol. Here, the message from drones is encrypted via Modified Light Weight Key Management (MLWKM) scheme. The key size of 16, the proposed method achieves lower (0.501) computational cost as compared to the other traditional schemes.
  Keywords: FANET; MLWKM; MECC; mutual authentication; batch authentication.
  DOI: 10.1504/IJVICS.2026.10079106
   
  
• Multi-vehicle logistics transportation route optimisation based on improved SCSO  
  by Qian Luo 
  Abstract: To achieve green and efficient multivehicle transportation route optimisation, an improved sand cat swarm optimisation algorithm is first designed to solve the problem. Subsequently, a dynamic multi-vehicle route optimisation model is established. A multi-objective scheduling function is constructed, in which the overall delivery cost is minimised by jointly considering fixed vehicle cost, route-dependent transportation cost, and carbon emission cost. A dynamic disturbance mechanism is introduced to cope with real-time task changes. In application testing, when the number of nodes was 100, the carbon emissions of the proposed method were 528.6 kg, the vehicle cost was CNY 35,820, the total cost was CNY 51,235, the number of vehicles was 13, and the average load rate was 82.7%, which was the best among the comparison methods. The research has provided feasible solutions and algorithm support for scheduling optimisation of multiple types of transportation resources.
  Keywords: multi-vehicle route optimisation; sand cat swarm optimisation algorithm; dynamic scheduling modelling; multi-objective optimisation; green logistics.
  DOI: 10.1504/IJVICS.2026.10080190
   
  
• PSA-YOLO: a lightweight vehicle detection algorithm integrating PConv and SA-NET attention  
  by Shaolin Qiu, Deng Shuchao, Honglei Pang, Wang Bo, Xiao Huangmei 
  Abstract: Autonomous driving systems require vehicle detection methods with both high accuracy and strong real-time performance. Lightweight models often struggle to balance speed and accuracy simultaneously on in-vehicle platforms. To address this issue, a lightweight improved YOLO model termed PSA-YOLO is developed, in which Partial Convolution (PConv) is adopted to reduce redundant computation and the Shuffle Attention Network (SA-NET) is incorporated to enhance discriminative feature representation while maintaining model efficiency. Built upon the YOLOv8n framework, the model enhances backbone and neck feature construction through the C2f-Faster module, which reduces redundant computation and improves feature interaction efficiency with a compact structure. To improve feature discrimination in complex environments, a lightweight SA-NET attention mechanism is incorporated to emphasise the salient characteristics of vehicle regions. Additionally, a bidirectional feature pyramid network (BiFPN) is adopted to redesign the multi-scale feature fusion pathway, enhancing the models ability to detect vehicles of different sizes. Experiments conducted on the KITTI dataset demonstrate that the proposed model contains 9.2M parameters and achieves an accuracy of 85.49%, representing a 2.16% gain compared with the original YOLOv8n. The method achieves improved detection performance without significantly increasing model complexity, making it practical for resource-constrained autonomous driving environments.
  Keywords: YOLOv8n; partial convolution; SA-NET; lightweight; vehicle detection; BiFPN.
  DOI: 10.1504/IJVICS.2026.10080471