A comprehensive survey on data dissemination in Vehicular Ad Hoc Networks

Shahwani, Hamayoun; Shah, Syed Attique; Ashraf, Muhammad; Akram, Muhammad; Jeong, Jaehoon; Shin, Jitae

doi:10.1016/j.vehcom.2021.100420

Cited by 50 publications

(30 citation statements)

References 95 publications

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“…However, the method by which intruders can locate the vehicles renders the scheme inapplicable. A message authentication protocol was proposed in [22] to boost VANET performance, but it has a high execution cost and is susceptible to impersonation, man-in-the-middle, illusion, modification, and plain-text attacks. In [23], we proposed a straightforward fuzzy-based system that recommends storage resources for vehicles based on factors like data size as well as time sensitivity.…”

Section: Security Analysis In Vanetmentioning

confidence: 99%

VANET Security Enhancement in Cloud Navigation with Internet of Things Based Trust Model in Deep Learning Architecture

Gnanajeyaraman

Arul

Miichael

et al. 2023

Preprint

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Many intelligent services are available for developing sensor-based vehicle-to-vehicle communication systems through vehicular ad hoc network (VANET). Although neighbour locating and interconnected vehicle sensor processes have been improved by geographic routing methods. However, reliability and data continuity among data routing are crucial for developing transportation systems due to the high level of mobility and realistic environment.The vehicles' wireless communication is also unrestricted and open, making them more vulnerable to security threats and compromising data for improper uses.This research propose novel technique in security improvement in VANET with vehicle cloud based navigation and trust model using deep learning techniques. the vehicle network navigation is carried out using cloud network integrated with IoT and its data transmission to the base station is analysed. then the navigated vehicle security is enhanced using trust based federated transfer quadratic authentication system. the experimental analysis is carried out based on number of vehicles in network as well as its security enhancement. the parameters analysed are throughput, data transmission rate, latency, network traffic analysis, scalability. the proposed technique attained throughput of 95%, data transmission rate of 67%, latency of 56%, network traffic analysis of 76%, scalability of 75%

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Section: Security Analysis In Vanetmentioning

confidence: 99%

VANET Security Enhancement in Cloud Navigation with Internet of Things Based Trust Model in Deep Learning Architecture

Gnanajeyaraman

Arul

Miichael

et al. 2023

Preprint

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“…Shahwani et al conducted a detailed literature assessment of existing data distribution systems in VANET, focusing on data‐related properties, safety, and other applications 11 . The work presented the readers with the necessary analysis of data transmission in VANET, highlighted potential possibilities and problems, and looked into current research related to data dissemination in VANET.…”

Section: Literature Reviewmentioning

confidence: 99%

Vehicular multihop intelligent transportation framework for effective communication in vehicular ad‐hoc networks

Theerthagiri

Krishnan

2022

Concurrency and Computation

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In the smart city, the presence of intelligent transportation systems (ITS) is much essential. The emerging vehicular ad-hoc networks (VANET) technology offers a wide range of applications in transportation, mobility, connectivity, and safety applications. In this decade, vehicular traffic is a prime hassle. The actual-instant traffic data to drivers along with navigation system would facilitate vehicles to select an excellent path. This article proposes hybrid VANET architecture for effective communication between vehicles. The proposed hybrid architecture uses the multihop routing algorithm to permit vehicles to enlarge their driving performance and road safety. The proposed hybrid vehicular multihop routing algorithm with intelligent transportation system (Hybrid VMR-ITS) allows the transportation system for instantaneous communications between vehicles and road-side units (RSUs) and vehicles-traffic servers effectively. The proposed work enhanced the whole spatial usage of a road network by reducing average vehicle travel costs with a reduced traffic overhead of 4%-9% compared with existing works.

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“…These solutions use only V2V vehicular communication to perform data dissemination and the simulation section presents a comparison among them. The surveys [7], [35]- [37] present extensive and up-to-date data dissemination protocols and algorithms for vehicular adhoc networks.…”

Section: Related Workmentioning

confidence: 99%

Toward an Efficient Data Dissemination Protocol for Vehicular Ad-Hoc Networks

Guidoni

Gottsfritz

Meneguette³

et al. 2022

IEEE Access

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Data Dissemination protocols are used for several vehicular applications, varying from warning messages to real-time video delivery. The majority of literature solutions consider the distance from the sender to choose the vehicle to forward the message. Basically, the solutions introduce a delay in the forwarding procedure, which is inversely proportional to the distance from the sender vehicle. In order to improve the forwarding procedure, this work introduces the concept of Road Covered Area to improve the overall data dissemination process and we describe how to calculate the road covered area by a node transmission. We present the D&RCA, the combination of Distance and Road Covered Area strategies to enhance the re-transmission during communication. Instead of considering the distance, we propose a function to combine the distance and road covered area to introduce a small delay before re-transmissions. We compare the proposed protocol with literature solutions considering the metrics of number of collisions, network coverage and communication latency for different density of vehicles in the network. When the network has 700 vehicles/km 2 , the data dissemination latency and number of collisions of the proposed D&RCA is, respectively, 1.24 and 1.32 times smaller than the literature solutions. When we increase the density of vehicles, all evaluated solutions present a network coverage above 90%.

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A comprehensive survey on data dissemination in Vehicular Ad Hoc Networks

Cited by 50 publications

References 95 publications

VANET Security Enhancement in Cloud Navigation with Internet of Things Based Trust Model in Deep Learning Architecture

VANET Security Enhancement in Cloud Navigation with Internet of Things Based Trust Model in Deep Learning Architecture

Vehicular multihop intelligent transportation framework for effective communication in vehicular ad‐hoc networks

Toward an Efficient Data Dissemination Protocol for Vehicular Ad-Hoc Networks

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