Modeling and Simulation of Data Dissemination in VANET Based on a Clustering Approach

Mohammed, Sura Jasim; Hasson, Saad Talib

doi:10.1109/csase51777.2022.9759671

Cited by 11 publications

(5 citation statements)

References 9 publications

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“…In this section, we delve into a comprehensive analysis that underscores the novelty of our work and clarifies the challenges in solving the delay problem for dissemination in VANETs through w-SMNO. Concurrently, we conduct a comparative study of the existing technologies, examining their impacts on transmission performance, including a consideration of the relay from the next hop without cluster formation [45], considering the challenge of a broadcast storm using a cluster-based forwarding mechanism [46], and route optimization for messages to their destination using particle swarm methods [47]. Our findings provide a notable reduction in delays, attributed to a substantial decrease in collisions and an enhanced success rate in message delivery facilitated via the implementation of the spider monkey technique.…”

Section: Discussionmentioning

confidence: 99%

A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning

Gupta,

Rathi

2024

Sensors

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The growth in linked and autonomous vehicles has led to the emergence of vehicular ad hoc networks (VANETs) as a means to enhance road safety, traffic efficiency, and passenger comfort. However, VANETs face challenges in facilitating trustworthiness and high-quality services due to communication delays caused by traffic, dynamic topology changes, variable speeds, and other influencing factors. Hence, there is a need for a reliable data dissemination scheme capable of reducing communication delays among hops by identifying effective forwarder nodes. In this paper, we propose a novel, weighted, estimated, spider monkey-based, nature-inspired optimization (w-SMNO) method to generate a set of efficient relays. Additionally, we introduce a dynamic weight assignment and configuration model to enhance system accuracy using a neural network based on backpropagation with gradient descent optimization techniques to minimize errors in the machine learning model. The w-SMNO also incorporates a distinct algorithm for effective relay selection among multiple monkey spider groups. The simulation results demonstrate substantial improvements in w-SMNO, with a 35.7% increase in coverage, a 41.2% reduction in the end-to-end delay, a 36.4% improvement in the message delivery rate, and a 38.4% decrease in the collision rate compared to the state-of-the-art approaches.

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Section: Discussionmentioning

confidence: 99%

A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning

Gupta,

Rathi

2024

Sensors

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“…Among them, hidden terminals, path loss, and other factors are also taken into account and used to ensure fast and stable dissemination of emergent messages. In [33]- [35], based on 802.11p, researchers used dedicated short-range communications (DSRC) for secure messaging. Unlike 5G and LIE, DSRC uses a WIFI architecture rather than a cellular network architecture for communication.…”

Section: Related Workmentioning

confidence: 99%

A V2V Emergent Message Dissemination Scheme for 6G-Oriented Vehicular Networks

Chen,

Chenyu,

et al. 2023

Chinese J. Elect.

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To ensure traffic safety and improve traffic efficiency, vehicular networks come up with multiple types of messages for safety and efficiency applications. In sixth-generation (6G) systems, these messages should be timely and error-free disseminated through vehicle-to-vehicle (V2V) communication to ensure traffic safety and efficiency. V2V supports direct communication between two vehicle user equipments, regardless of whether a base station is involved. We propose a packet delivery ratio (PDR)-based message dissemination scheme (PDR-MD) between V2V in 6G-oriented vehicular networks to select relay vehicles when broadcasting emergent messages. This scheme grasps the balance between vehicle distance and PDR so as to reduce transmission delay while ensuring reliable PDR. We compared the PDR-MD scheme with other probabilistic broadcasting schemes. The experimental results show that the PDR-MD protocol can maintain close to 95% and above PDR in transmitting emergent messages, and the transfer rate stays below 40%.

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“…The mobility of cars, however, is one of the elements that have a considerable impact on the architecture of these networks. Furthermore, because different vehicles have unique mobility characteristics in urban settings, it becomes much more complicated [ 2 ]. In this regard, it is crucial to make use of knowledge of these vehicles’ movement to offer strong solutions and a variety of applications [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Data Dissemination in VANETs Using Particle Swarm Optimization

Desai

El-Ocla

Purohit

2023

Sensors

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A vehicular Ad-Hoc Network (VANET) is a type of Mobile Ad-Hoc Networks (MANETs) that uses wireless routers inside each vehicle to act as a node. The need for effective solutions to urban traffic congestion issues has increased recently due to the growing number of automobile connections in the car communications system. To ensure a high level of service and avoid unsafe situations brought on by congestion or a broadcast storm, data dissemination in a VANET network requires an effective approach. Effective multi-objective optimization methods are required to tackle this because of the implied competing nature of multi-metric approaches. A meta-heuristic technique with a high level of solution interactions can handle efficient optimization. To accomplish this, a meta-heuristic search algorithm particle optimization was chosen. In this paper, we have created a network consisting of vehicles as nodes. The aim is to send emergency messages immediately to the stationary nodes. The normal messages will be sent to the FIFO queue. To send these messages to a destination node, multiple routes were found using Time delay-based Multipath Routing (TMR) method, and to find the optimal and secure path Particle Swarm Optimization (PSO) is used. Our method is compared with different optimization methods such as Ant Colony Optimization (ACO), Firefly Optimization (FFO), and Enhanced Flying Ant Colony Optimization (EFACO). Significant improvements in terms of throughput and packet loss ratio, reduced end-to-end delay, rounding overhead ratio, and the energy consumption are revealed by the experimental results.

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Modeling and Simulation of Data Dissemination in VANET Based on a Clustering Approach

Cited by 11 publications

References 9 publications

A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning

A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning

A V2V Emergent Message Dissemination Scheme for 6G-Oriented Vehicular Networks

Data Dissemination in VANETs Using Particle Swarm Optimization

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