Cited by 96Vehicular Ad Hoc Networks (VANETs)IoT and Edge/Fog ComputingSoftware-Defined Networks and 5G

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End-to-End V2X Latency Modeling and Analysis in 5G Networks

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Published version of a preprint

Abstract

5G networks provide higher flexibility and improved performance compared to previous cellular technologies. This has raised expectations on the possibility to support advanced Vehicle to Everything (V2X) services using the cellular network via Vehicle-to-Network (V2N) and Vehicle-to-Network-to-Vehicle (V2N2V) connections. The possibility to support critical V2X services using 5G V2N2V or V2N connections depends on their end-to-end (E2E) latency. The E2E latency of V2N2V or V2N connections depends on the particular 5G network deployment, dimensioning and configuration, in addition to the network load. To date, few studies have analyzed the capabilities of V2N2V or V2N connections to support critical V2X services, and most of them focus on the 5G radio access network or consider dedicated 5G pilot deployments under controlled conditions. This paper progresses the state-of-the-art by introducing a novel E2E latency model to quantify the latency of 5G V2N and V2N2V communications. The model includes the latency introduced at the radio, transport, core, Internet, peering points and application server (AS) when vehicles are supported by a single mobile network operator (MNO) and when they are supported by multiple MNOs. The model can quantify the latency experienced when the V2X AS is deployed from the edge of the network (using MEC platforms) to the cloud. Using this model, this study estimates the E2E latency of 5G V2N2V connections for a large variety of possible 5G network deployments and configurations. The analysis helps identify which 5G network deployments and configurations are more suitable to meet V2X latency requirements. To this aim, we consider as a case study the cooperative lane change service. The conducted analysis highlights the challenge for centralized network deployments that locate the V2X AS at the cloud to meet the latency requirements of advanced V2X services. Locating the V2X AS closer to the cell edge reduces the latency. However, it requires a higher number of ASs and also a careful dimensioning of the network and its configuration to ensure sufficient network and AS resources are dedicated to serve the V2X traffic.

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  • The model introduced in this paper can complement end-to-end 5G analysis.

    “As such, The model introduced in this paper model can complement end-to-end 5G analysis, such as the one presented in [14].”

    From Cross-layer latency analysis for 5G NR in V2X communications (2025) · cites this paper as [14]

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References 16 · Cited by 96

Research works printed but not linked: 2

  1. Bertsekas, 1992, Data Networks (Chapter 3. Delay Models in Data Networks)
  2. Pujol, 2021, 5G Observatory quarterly report 11: Up to March 2021

Metadata

Authors
Coll-Perales, B., Lucas-Estañ, M. C., Shimizu, T., Gozalvez, J., Higuchi, T., Avedisov, S., Altintas, O., & Sepulcre, M.
Affiliations
  • Universitat de Miguel Hernández d'Elx (ES)
  • Toyota Motor North America (United States) (US)
  • Universidad Miguel Hernández de Elche, Alicante, Spain
Venue
IEEE Transactions on Vehicular Technology
Published
2023-04
Volume
72
Issue
4
Pages
5094-5109
ISSN
  • 0018-9545 (ISSN-L)
  • 1939-9359
OpenAlex
W4312526381
Cited by
96
References
16
Citations by year
2026: 22 · 2025: 32 · 2024: 23 · 2023: 16
FWCI
5.07
Type
journal article
Language
en
Open access
Locations
  • IEEE Transactions on Vehicular Technology (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • MCIN/AEI (10.13039/501100011033, IJC2018-036862-I, PID2020-115576RB-I00)
  • Generalitat Valenciana (GV/2021/044, CIGE/2021/096)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
Keywords
vehicle-to-everything communication, end-to-end delay, 5G, latency modeling, edge computing, mobile edge computing, network dimensioning, multi-operator networks

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