Geometric Shapes-based PSO Approach for Routing in Vehicular Networks

Dhurandher, Sanjay Kumar; Singh, Jagdeep; Woungang, Isaac; Gupta, Mrigali; Sabharwal, Nakul

doi:10.1109/africon46755.2019.9134043

Cited by 3 publications

(2 citation statements)

References 31 publications

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“…In class, the optimal number of sets is found in the maximum transmission range. Dhurandher et al (2019) Proposed a geometric shape based PSO approach for Routing. GPSV proposed technique uses the angle between the node and determines the best suitable route to transfer the data.…”

Section: Literature Reviewmentioning

confidence: 99%

A PSO Enable Multi-Hop Clustering Algorithm for VANET

Temurnikar

Verma

2021

International Journal of Swarm Intelligence Research

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VANET (Vehicle Ad-hoc Network) is an emerging technology in today’s intelligent transport system. In VANET, there are many moving nodes which are called the vehicle running on the road. They communicate with each other to provide the information to driver regarding the road condition, traffic, weather and parking. VANET is a kind of network where moving nodes talk with each other with the help of equipment. There are various other things which also make complete to VANET like OBU (onboard unit), RSU (Road Aside Unit) and CA (Certificate authority). In this paper, a new PSO enable multi-hop technique is proposed which helps in VANET to Select the best route and find the stable cluster head and remove the malicious node from the network to avoid the false messaging. The false can be occurred when there is the malicious node in a network. Clustering is a technique for making a group of the same type node. This proposed work is based on PSO enable clustering and its importance in VANET. While using this approach in VANET, it has increased the 20% packet delivery ratio.

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Section: Literature Reviewmentioning

confidence: 99%

A PSO Enable Multi-Hop Clustering Algorithm for VANET

Temurnikar

Verma

2021

International Journal of Swarm Intelligence Research

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“…Several optimization algorithms are used in the recent days such as Particle Swarm Optimization (PSO) [4] and Genetic Algorithm (GA) [5]. But applying a single optimization technique in high speed dynamically varying VANETs network will not produce effective performance.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Bio-Inspired Optimization Scheme for RSU Distribution in Vehicular Ad-Hoc Network

Hassan¹,

Al-obaidi²,

Alani³

et al. 2023

IJETAE

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—Vehicular Ad-Hoc Network (VANETs) is a trending modelthat plays maximum role inall the application of Intelligent Transport Systems (ITS). In general, VANETs are based on two communication types such as among vehicles and vehicles to infrastructure Roadside Units(RSU) based communication. In this paper, HACOGO approach is developedbased on ahybrid bio inspired optimization with the combination of Ant Colony Optimization (ACO) with Grasshopper Optimization Algorithm (GOA). The HACOGO is used to perform stable RSU distribution in VANETs. The ACO algorithm is used to help the vehicle to select the optimal path toward the destination and GOA algorithm highly magnificent vehicle is chosen as RSU. The Performance analysis of HACOGO is done by calculating the common parameters such as packet delivery ratio, end-to-end delay, packet loss and routing overhead. To analysis the effectiveness of the proposed model its results are compared with the earlier works. From the outcome it is proven using the HACOGO approach the end-to-end delay, packet loss and routing overhead is reduced as well as the packet delivery ratio of the network is increased than others. Keywords—Vehicular Ad-Hoc Network,Roadside Units, Ant Colony Optimization.

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The Evolution of Intelligent Transportation Systems: Analyzing the Differences and Similarities between IoV and IoFV

Herich,

Vaščák

2024

Drones

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The Internet of Vehicles (IoV) and the Internet of Flying Vehicles (IoFV) are integral components of intelligent transportation systems with the potential to revolutionize the way we move people and goods. Although both the IoV and IoFV share a common goal of improving transportation efficiency, safety, and sustainability, they possess distinct characteristics and face unique challenges. To date, the existing literature has predominantly focused on specific aspects of either the IoV or IoFV, but a comprehensive review comparing and contrasting the two domains is still lacking. This review paper aims to address this gap by providing an in-depth analysis of the key differences between the IoV and IoFV systems. The review will examine the technological components, network infrastructure, communication protocols, data management, objectives, applications, challenges, and future trends associated with both domains. Additionally, this paper will explore the potential impact of technologies such as artificial intelligence, machine learning, and blockchain. Ultimately, the paper aims to contribute to a deeper understanding of the implications and potential of these technologies, both in the context of transportation systems and beyond.

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Geometric Shapes-based PSO Approach for Routing in Vehicular Networks

Cited by 3 publications

References 31 publications

A PSO Enable Multi-Hop Clustering Algorithm for VANET

A PSO Enable Multi-Hop Clustering Algorithm for VANET

A Hybrid Bio-Inspired Optimization Scheme for RSU Distribution in Vehicular Ad-Hoc Network

The Evolution of Intelligent Transportation Systems: Analyzing the Differences and Similarities between IoV and IoFV

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