A Framework for Performance Evaluation of VANETs Using NS-3 Simulator

Malnar, Marija; Jevtić, Nenad

doi:10.7307/ptt.v32i2.3227

Cited by 7 publications

(6 citation statements)

References 31 publications

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“…Throughput, packet delivery functions and packet sizes are parameters that have been evaluated. Malnar et al [29] developed an NS-3-based vehicular network framework to analyze performance metrics such as throughput and packet loss. Several topology-based routing protocols were compared and Expected Transmission Number (ETX) metric was proposed to improve performance.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Internet of Vehicles Mesh Networks Based on Actual Switch Models

Hu,

Ren,

Cheng

et al. 2024

Electronics

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The rapid growth of the automotive industry has exacerbated the conflict between the complex traffic environment, increasing communication demands, and limited resources. Given the imperative to mitigate traffic and network congestion, analyzing the performance of Internet of Vehicles (IoV) mesh networks is of great practical significance. Most studies focus solely on individual performance metrics and influencing factors, and the adopted simulation tools, such as OPNET, cannot achieve the dynamic link generation of IoV mesh networks. To address these problems, a network performance analysis model based on actual switches is proposed. First, a typical IoV mesh network architecture is constructed and abstracted into a mathematical model that describes how the link and topology changes over time. Then, the task generation model and the task forwarding model based on actual switches are proposed to obtain the real traffic distribution of the network. Finally, a scientific network performance indicator system is constructed. Simulation results demonstrate that, with rising task traffic and decreasing node caching capacity, the packet loss rate increases, and the task arrival rate decreases in the network. The proposed model can effectively evaluate the network performance across various traffic states and provide valuable insights for network construction and enhancement.

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Section: Related Workmentioning

confidence: 99%

Performance Analysis of Internet of Vehicles Mesh Networks Based on Actual Switch Models

Hu,

Ren,

Cheng

et al. 2024

Electronics

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“…Network Simulator ns-3 [83][84][85][86], an open-source, event-driven simulator designed specifically for research in computer communication networks, offers a suite of validation tests to verify the accuracy and reliability of its simulation components. These tests are run daily on the ns-3 snapshot to ensure consistent performance and quality.…”

Section: An Overview Of Network Simulator Ns-3 Validation Suitementioning

confidence: 99%

Augmenting Vehicular Ad Hoc Network Security and Efficiency with Blockchain: A Probabilistic Identification and Malicious Node Mitigation Strategy

Juárez,

Bordel

2023

Electronics

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This manuscript delineates the development of an avant garde dual-layer blockchain architecture, which has been meticulously engineered to augment the security and operational efficacy of vehicular ad hoc networks (VANETs). VANETs, which are integral to the infrastructure of intelligent transport systems, facilitate the critical exchange of information between vehicular nodes. Despite their significance, these networks confront an array of formidable security vulnerabilities. Our innovative approach, employing a dual blockchain framework—the event chain and the reputation chain—meticulously tracks network activities, thereby significantly enhancing the trustworthiness and integrity of the system. This research presents a transformative dual-layer blockchain architecture, which was conceived to address the intricate security challenges pervasive in VANETs. The architecture pivots on a sophisticated reputation assessment framework, thus leveraging the principles of Bayesian inference and the analytical rigor of historical data to markedly diminish observational errors, as well as elevate the accuracy of reputation evaluations for vehicular nodes. A salient feature of our methodology is the implementation of an attenuation factor, which has been deftly calibrated to modulate the impact of historical behaviors on current reputation scores, thereby ensuring their relevance and alignment with recent vehicular interactions. Additionally, the numerical threshold serves as an indispensable mechanism, thus establishing a definitive criterion for the early identification of potentially malicious activities and enabling the activation of proactive security measures to safeguard the network’s integrity. Empirical validation of our dual-layer blockchain model has yielded a remarkable 86% efficacy in counteracting malevolent behaviors, thus significantly outperforming extant paradigms. These empirical outcomes underscore the model’s potential as a vanguard in the domain of secure and efficient reputation management within VANETs, thereby heralding a substantial advancement in the sphere of intelligent transportation systems.

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“…Recently, many researchers have utilized nature-inspired algorithms for selecting the optimal routes in VANETs. Some commonly used nature-inspired algorithms are PSO, flower pollination algorithm, GA, artificial bee colony algorithm, ACO, Cuckoo search, bat algorithm, and Firefly Algorithm (FA) [12,13]. In [2].…”

Section: Related Work a Background Informationmentioning

confidence: 99%

Hybrid Genetic Firefly Algorithm-Based Routing Protocol for VANETs

et al. 2022

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Vehicular Adhoc Networks (VANETs) are used for efficient communication among the vehicles to vehicle (V2V) infrastructure. Currently, VANETs are facing node management, security, and routing problems in V2V communication. Intelligent transportation systems have raised the research opportunity in routing, security, and mobility management in VANETs. One of the major challenges in VANETs is the optimization of routing for desired traffic scenarios. Traditional protocols such as Adhoc Ondemand Distance Vector (AODV), Optimized Link State Routing (OLSR), and Destination Sequence Distance Vector (DSDV) are perfect for generic mobile nodes but do not fit for VANET due to the high and dynamic nature of vehicle movement. Similarly, swarm intelligence routing algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) routing techniques are partially successful for addressing optimized routing for sparse, dense, and realistic traffic network scenarios in VANET. Also, the majority of metaheuristics techniques suffer from premature convergence, being stuck in local optima, and poor convergence speed problems. Therefore, a Hybrid Genetic Firefly Algorithm-based Routing Protocol (HGFA) is proposed for faster communication in VANET. Features of the Genetic Algorithm (GA) are integrated with the Firefly algorithm and applied in VANET routing for both sparse and dense network scenarios. Extensive comparative analysis reveals that the proposed HGFA algorithm outperforms Firefly and PSO techniques with 0.77% and 0.55% of significance in dense network scenarios and 0.74% and 0.42% in sparse network scenarios, respectively.

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A Framework for Performance Evaluation of VANETs Using NS-3 Simulator

Cited by 7 publications

References 31 publications

Performance Analysis of Internet of Vehicles Mesh Networks Based on Actual Switch Models

Performance Analysis of Internet of Vehicles Mesh Networks Based on Actual Switch Models

Augmenting Vehicular Ad Hoc Network Security and Efficiency with Blockchain: A Probabilistic Identification and Malicious Node Mitigation Strategy

Hybrid Genetic Firefly Algorithm-Based Routing Protocol for VANETs

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