Effect of RSU Placement on Autonomous Vehicle V2I Scenarios

Kara, Barış; Özgövde, Bahri Atay

doi:10.17694/bajece.668615

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…The limitation of the algorithm is that the authors did not consider the mobility of nodes between the cell towers. The authors of [25] introduced a secure protocol for SDN VANETs based on elliptic curve cryptography and hashing to provide security between the RSU and SDN controller using the Scyther tool. However, it works only for single V2V communications and not for multiple vehicles.…”

Section: Edge and Fog Computing Solutions For Scpp Problemmentioning

confidence: 99%

Real-Time IoV Task Offloading through Dynamic Assignment of SDN Controllers: Algorithmic Approaches and Performance Evaluation

Lanka,

Kandasamy

2023

IJRITCC

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Task offloading in Internet of Vehicles (IoV) is very crucial. The widespread use of IoT applications frequently interacts with the cloud, thereby increasing the load on centralized cloud controllers. Centralized network management in cloud infrastructure is not feasible for the latest IoT trends. Decentralized and decoupled network management in Software Defined Networks (SDN) can enhance IoV services. SDN and IoV coupling can better handle task offloading in ubiquitous and dynamic IoV environments. However, appropriate SDN controller assignment and allotment strategies play a prominent role in IoV communication. In this study, we developed algorithms for SDN controller assignment and allotment namely 1) Next Fit Allotment and Assignment of SDN Controller in IoV (NFAAC), 2) Dynamic Bin Packing Allotment and Assignment of SDN Controller in IoV (DBPAAC), and 3) Dynamic Focused and Bidding Allotment and Assignment algorithm of SDN Controller in IoV (DFBAAC). These algorithms were simulated using open-flow switch controllers. The controllers were modeled as Road Side Units (RSU) that can allocate bandwidth and resource requirements to vehicles on the road. Our results show that our proposed algorithm works efficiently for SDN controller assignment and allocation, outperforming the existing work by a significant improvement of 13.5%. The working of the proposed algorithms are verified, tested, and analytically presented in this study.

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Section: Edge and Fog Computing Solutions For Scpp Problemmentioning

confidence: 99%

Real-Time IoV Task Offloading through Dynamic Assignment of SDN Controllers: Algorithmic Approaches and Performance Evaluation

Lanka,

Kandasamy

2023

IJRITCC

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“…A RSU deployment strategy was proposed for addressing the issue of computational demand and network coverage during placement. 18 This RSUs deployment framework was proposed for generating different number of placement models through the characteristics of area targeted for installation. It was utilized the infrastructure providers who played a vital role in the design of smart city.…”

Section: Related Workmentioning

confidence: 99%

Chew's first Delaunay triangulation refinement scheme‐based positioning of road side units for optimal network coverage in vehicular ad‐hoc networks

Selvakumari¹,

Lakshmi²,

Sheela

et al. 2022

Int J Communication

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Summary The temporal network fragmentation and uncertain vehicle mobility are considered to impact the communication connectivity among the vehicular nodes of the network. In this context, road side units (RSUs) play an anchor role in enhancing the vehicle‐to‐vehicle (V2V) communication connectivity and support vehicle‐to‐infrastructure (V2I) communication. In the current scenario, deploying a huge number of RSUs in the vehicular networks at an initial stage is completely impossible as it incurs high installation cost and authority restriction. Moreover, the optimal placement of RSUs in the vehicular network needs to be enforced for attaining maximized network coverage. In this paper, Chew's first Delaunay triangulation refinement scheme (CFDTRS) is proposed for optimal positioning of RSUs in order to attain optimal network coverage in the vehicular network with minimized cost. This CFDTRS considered the factors of vehicular density, number of obstacles in the map, intersection popularity, and global coverage into account during the placement of RSUs. It is proposed with the objective of deploying required number of RSUs within the range of data transmission in order to achieve maximal coverage in the convex map, such that each area of the convex map is completely covered with at least a single RSU in the existence of multiple number of obstacles. The simulation results of the proposed CFDTRS attained from the real time situations of simplex, moderate, and complex maps confirmed improved packet delivery rate of 9.32%, throughput by 10.74% with minimized packet loss of 9.14%, and reduced end‐to‐end delay of 19.31$, compared to the benchmarked schemes considered for investigation.

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“…A RSU deployment strategy was proposed for addressing the issue of computational demand and network coverage during placement [21]. This RSUs deployment framework was proposed for generating different number of placement models through the characteristics of area targeted for installation.…”

Section: Related Workmentioning

confidence: 99%

Chews First Delaunay Triangulation refinement Scheme-Based Positioning of RSUs for Optimal Network Coverage in VANETs

Selvakumari¹,

Lakshmi²,

Sheela³

et al. 2021

Preprint

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The temporal network fragmentation and uncertain vehicle mobility are considered to impact the communication connectivity among the vehicular nodes of the network. In this context, Road Side Units (RSUs) play an anchor role in enhancing the vehicle-to-vehicle (V2V) communication connectivity and support Vehicle-to-Infrastructure (V2I) communication. In the current scenario, deploying a huge number of RSUs in the vehicular networks at an initial stage is completely impossible as it incurs high installation cost and authority restriction. Moreover, the optimal placement of RSUs in the vehicular network needs to be enforced for attaining maximized network coverage. In this paper, Chews First Delaunay Triangulation Refinement Scheme (CFDTRS) is proposed for optimal positioning of RSUs in order to attain optimal network coverage in the vehicular network with minimized cost. This CFDTRS considered the factors of vehicular density, number of obstacles in the map, intersection popularity and global coverage into account during the placement of RSUs. It is proposed with the objective of deploying required number of RSUs within the range of data transmission in order to achieve maximal coverage in the convex map, such that each area of the convex map is completely covered with at least a single RSU in the existence of multiple number of obstacles. The simulation results of the proposed CFDTRS attained from the real time situations of simplex, moderate and complex maps confirmed improved packet delivery rate of 9.32%, throughput by 10.74% with minimized packet loss of 9.14% and reduced end-to-end delay of 19.31$, compared to the benchmarked schemes considered for investigation.

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Effect of RSU Placement on Autonomous Vehicle V2I Scenarios

Cited by 4 publications

References 25 publications

Real-Time IoV Task Offloading through Dynamic Assignment of SDN Controllers: Algorithmic Approaches and Performance Evaluation

Real-Time IoV Task Offloading through Dynamic Assignment of SDN Controllers: Algorithmic Approaches and Performance Evaluation

Chew's first Delaunay triangulation refinement scheme‐based positioning of road side units for optimal network coverage in vehicular ad‐hoc networks

Chews First Delaunay Triangulation refinement Scheme-Based Positioning of RSUs for Optimal Network Coverage in VANETs

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