International Journal of Vehicle Information and Communication Systems (9 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.
  
  
• Bayesian optimised route and SOH estimation effect for Li-ion battery management system of electric vehicles based on LSTM  
  by Zhijun Xiao 
  Abstract: Lithium-ion batteries are widely used in electric vehicles, and accurate state of health (SOH) estimation is crucial for driving safety. This study applies a long short-term memory (LSTM) algorithm to model SOH based on health features correlated with standardised capacity. Since manual parameter tuning is inefficient and training is time-consuming with large datasets, a domain space design inspired by manual adjustment is combined with Bayesian optimisation for hyperparameter configuration. Experimental results show that the optimised LSTM improves estimation accuracy by 0.0235%. Compared with grid and random search, Bayesian optimisation reduces relative error by 50.63% on average and requires the least time, demonstrating both higher optimisation efficiency and near-optimal parameter selection.
  Keywords: LSTM; lithium battery management system; Bayesian optimisation algorithm; SOH estimation; battery health characteristics.
  DOI: 10.1504/IJVICS.2025.10073695
   
  
• Estimating road profiles using functional observer: a half-vehicle model approach  
  by Mohamed Saber, Mohamed Ouahi, Ghali Naami, El Akchioui Nabil 
  Abstract: To guarantee both driver and vehicle safety when driving and to avoid different kinds of accidents, particularly rollover accidents, which may culminate in catastrophic consequences, it becomes essential that drivers have as precise comprehension of the variables that influence vehicle as possible. The nonmeasured variables in the system state are estimated using a half-vehicle model that includes an unknown input functional observer, allowing one to precisely estimate the unknown inputs such the road profile characteristic. With the assistance of Lyapunov-Krasovskii stability theory, convergence conditions, and a solution of linear matrix inequalities (LMIs), the suggested functional observer design constraints are developed in order to accomplish the goal of minimizing the estimation error convergent to zero, which ultimately results in a more accurate determination of the observer parameters. Furthermore, a simulation that accurately evaluates vehicles variable’s estimation and changing road conditions prediction has been implemented. By developing advanced vehicle control and monitoring systems as a whole this research makes a substantial contribution to the field of road safety.
  Keywords: vehicle dynamics; functional observer; state estimation; road profile estimation; half-vehicle model.
  DOI: 10.1504/IJVICS.2025.10074228
   
  
• Application of vehicle trajectory big data analysis based on DPCS algorithm  
  by Jinzhe Wang 
  Abstract: The collection and analysis of vehicle trajectory data has become increasingly important not only to provide real-time information on traffic flow and patterns, but also because it has significant implications for optimising traffic management, reducing congestion and improving road safety. This study proposes a vehicle trajectory big data analysis method based on density peak clustering algorithm and conducts simulation experiments to verify it. The results showed that the dual population cuckoo search algorithm performed well in optimising the Rasterikin, Rosenbrock and Ackley functions, finding near optimal solutions of -1.8560, 0.0001 and 0.0002 within 55, 105 and 85 iterations, respectively. In the 20 to 100 dimensional space, the algorithm converged quickly, the solution was stable, the average solution was about 123.54 and the standard deviation was 2.36. In the NuScenes data set experiment, the DPCS algorithm maintained a stable accuracy of 0.9 to 1.0 after 12 rounds of training, outperforming the comparison algorithms and demonstrating its reliability in object detection. The analysis method is of great significance for improving the operational efficiency and safety of the transportation system.
  Keywords: DPCS algorithm; vehicle trajectory; big data: CS algorithm; PCS algorithm.
  DOI: 10.1504/IJVICS.2025.10073549
   
  
• Data storage and sharing for the internet of vehicles and GPBFT consensus algorithm  
  by Jiyan Zhou, Jinfeng Liu 
  Abstract: This study constructs a secure and efficient data storage and sharing architecture for the Internet of Vehicles. A practical Byzantine fault-tolerant consensus algorithm using reputation was proposed to address the shortcomings of roadside unit equipment in the architecture. The experimental results showed that in the performance verification of reinforced data storage, the storage proportion of the research scheme was always lower than that of the comparison algorithm. In the simulated 5000 transactions, it was always lower than 40 MB, while the comparison algorithm reached a maximum of 72 MB. The efficiency of querying registration information and vehicle data increased by 38.2% and 49.1%, respectively. In the shared performance verification, the fully loaded roadside unit devices decreased by a maximum of 2.8%. Under heavy load conditions, the fully loaded nodes decreased by a maximum of 20.7%. In the validation of the proposed consensus algorithm, its performance was more stable in terms of throughput, and the number of transactions processed per second by d (10) remained basically between 380 and 640. Overall, the constructed secure and efficient data storage and sharing architecture for the Internet of Vehicles is efficient and secure, which can be effectively applied in practical IoV systems.
  Keywords: internet of vehicles; GPBFT; road side unit equipment; throughput; malicious nodes.
  DOI: 10.1504/IJVICS.2024.10072357
   
  
• Optimisation of freight vehicle routes leveraging cloud computing and edge endpoints  
  by Hongxia Jin 
  Abstract: In the current freight industry, how to improve the economic benefits of freight transportation and solve the problem of insufficient information timeliness under cloud computing is a persistent challenge. In response to the problems of delayed information in cloud computing path planning and insufficient economic benefits of planning results, this study proposes a freight vehicle path optimisation model supported by cloud computing and edge end. This model introduces edge computing into cloud platforms and constructs a genetic algorithm-based truck path optimisation algorithm. According to test outcomes, the path planning time of the proposed model was at most 160 ms lower than that of a regular cloud computing environment. In simulation testing, the optimised path planning model saved a total cost of 16.8% compared to the pre optimised output. The proposed model effectively optimises the economic benefits of freight transportation and solves the problem of insufficient information timeliness.
  Keywords: cloud computing; edge end; path optimisation; iteration; logistics.
  DOI: 10.1504/IJVICS.2024.10072356
   
  
• Performance analysis of dual-hop DF multi-relay communication applying TAS/MRC and JTRAS system over Fisher-Snedecor F fading channels  
  by Hubha Saikia, Rajkishur Mudoi 
  Abstract: In this paper, the Outage Probability (OP), Bit-Error-Rate (BER) and ergodic capacity of dual-hop and Decode-and-Forward (DF) type multi-relay aided communication system subject to Fisher-Snedecor F fading channel are analysed. The Multiple-Input-Multiple-Output (MIMO) technique is utilised in the communication system. The MIMO system can upgrade the system performance, but such a method uses plenty of antennas, thereby increasing the cost and hardware ramifications of the system. In this article, to prevail over these problems, at first the Transmit Antenna Selection (TAS) is utilised for the transmission of signals along with the Maximal Ratio Combining (MRC) diversity receiver. In the second method, a Joint Transmit and Receive Antenna Selection (JTRAS) diversity scheme is applied for communication. The expressions of OP, BER and ergodic capacity are obtained concerning TAS/MRC as well as JTRAS type MIMO systems. The OP and the BER expressions are derived using the Cumulative Distribution Function (CDF) of instantaneous SNR. The expression of channel capacity is obtained using the Probability Density function (PDF) of instantaneous SNR. The obtained expressions are verified by using Monte-Carlo simulation.
  Keywords: BER; cooperative communication; dual-hop; decode-and-forward; joint transmit and receive antenna; maximal ratio combining.
  DOI: 10.1504/IJVICS.2025.10070719
   
  
• Innovative approach to detect wormhole attack from vehicular ad-hoc network by using variable control chart  
  by Shahjahan Ali, Parma Nand, Shailesh Tiwari, Kumari Hemlata 
  Abstract: The wireless nature of Vehicular Ad-hoc Network (VANET) has made it more sensitive towards various types of attacks. Wormhole is one of the attacks by which the security of VANET's routing may be disturbed. In this research paper an innovative approach based on variable control chart is proposed to detect the wormhole attack from VANET. Variable control chart is used in industry to judge the quality of predefined process. This approach can detect misbehaving (i.e., wormhole, black hole) nodes in real time by applying the monitoring system at every receiving node within the network. Here, SUMO 0.32.0 and NS-2.35 simulators are used. The results signify that the proposed approach is capable to detect the wormhole attack on VANET. The novelty of this research work is that a new approach based on variable control chart is used to make the VANET more secure by detecting the wormhole attack on VANET.
  Keywords: VANET; vehicular ad-hoc network; routing; wormhole; network; SUMO 0.32.0; NS-2.35; attack.
  DOI: 10.1504/IJVICS.2025.10072857