Network Performance Analysis of Content Delivery for V2R Communication in VANET Urban Mobility
Abstract
Vehicular ad hoc networks (VANETs) are undoubtedly in demand as a medium to support a broad range of applications ranging from safety, transport efficiency, to even infotainment. As the assortment of heterogeneous content rises in range and number, its content delivery also expands to vehicles and their onboard users, forcing the VANET paradigm to evolve from delivering simple safety and warning messages to unconventional applications with content delivery necessities. Information, advertisement, and entertainment applications enrich its content with various types of media which in turn, produce large content and are challenging many aspects of VANET capabilities. One of the issues of content delivery in VANET involves its V2R communication that will be congested due to the high density of vehicles, especially in an urban scenario, hence delay the transmission of the content delivery. VANET performance was simulated and analyzed based on content delivery services for V2R communication with several traffic congestion scenarios in urban mobility environment centered to matrices such as latency, packet loss, network throughput, etc. The results from the experiments determined that the content of smaller packet size is better than large packet size with low vehicle density as it impacts the content delivery for V2R communication by having low packet loss and network latency.
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Vehicle-to-roadside communication enables communication with roadside sensors, cameras, and other infrastructure elements, helping drivers to make informed decisions and enhancing overall road safety and convenience.
“Vehicle-toroadside (V2R) communication enables communication with roadside sensors, cameras, and other infrastructure elements, helping drivers to make informed decisions and enhancing overall road safety and convenience [10].”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [10]
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Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy
Zhang, X., Li, J., Zhou, J., Zhang, S., Wang, J., Yuan, Y., Liu, J., & Li, J. (2025) · Automotive Innovation · doi:10.1007/s42154-024-00310-2 · Cited by 103 · see citing works
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- Authors
- Ramli, N. I., Shawal, S., Ibrahim, M. F., & Rawi, M. I. M.
- Affiliations
- Universiti Teknologi MARA System (MY)
- Venue
- 2021 IEEE International Conference on Computing (ICOCO)
- Publisher
- IEEE
- Published
- 2021-11-17
- Volume
- 16
- Pages
- 129-133
- OpenAlex
- W4206504939
- Cited by
- 2
- References
- 14
- Citations by year
- 2025: 1 · 2023: 1
- FWCI
- 0.39
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE International Conference on Computing (ICOCO) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Computer Science › Computer Networks and Communications › Opportunistic and Delay-Tolerant Networks
- Keywords
- vehicular ad hoc networks, content distribution, urban mobility, traffic congestion, packet loss, latency, network throughput, packet size, traffic density
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