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Updated: Jul 12, 2026

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Urban Advanced Mobility Dependability: A Model-Based Quantification on Vehicular Ad Hoc Networks with Virtual Machine

Luis Guilherme Silva1, Israel Cardoso1, Carlos Brito1

  • 1Coordination of the Information Systems Course, Technical College of Teresina (CSHNB), Federal University of PiauĂ­ (UFPI), Picos 64049-550, PiauĂ­, Brazil.

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|December 9, 2023
PubMed
Summary

This study introduces a new Stochastic Petri Nets method to enhance the reliability and availability of Vehicular Ad Hoc Networks (VANETs). This improves urban advanced mobility (UAM) systems by optimizing vehicle communication and control.

Keywords:
Stochastic Petri Nets (SPN)Vehicular Ad Hoc Networks (VANETs)dependability modelingnetwork reliability and availabilityvirtual machine migration

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Transportation Systems

Background:

  • Vehicular Ad Hoc Networks (VANETs) are essential for advanced urban mobility (UAM) but require enhanced reliability and availability.
  • Integrating UAM into urban infrastructures necessitates robust communication and control architectures.
  • Current VANET evaluation methods may not fully address the dynamic demands of UAM.

Purpose of the Study:

  • To propose and evaluate a novel Stochastic Petri Nets (SPN) method for assessing VANET-based Vehicle Communication and Control (VCC) architectures.
  • To incorporate Edge Computing and virtual machine migration into the SPN model for realistic VANET integration.
  • To provide a cost-effective framework for optimizing VANET reliability and availability for UAM.

Main Methods:

  • Development of a novel Stochastic Petri Nets (SPN) model for VANET evaluation.
  • Integration of virtual machine migration and Edge Computing concepts within the SPN framework.
  • Application of Design of Experiments (DoE) for sensitivity analysis of SPN model parameters.

Main Results:

  • The SPN model effectively quantifies VANET reliability and availability for UAM integration.
  • Case studies demonstrate the model's capability to provide insights into system performance.
  • Sensitivity analysis identified key parameters influencing system availability, crucial for UAM efficiency.

Conclusions:

  • The proposed SPN method offers a significant advancement in evaluating and optimizing VANETs for UAM.
  • This research provides a reliable and cost-effective framework for monitoring UAM systems in future urban environments.
  • The findings are critical for enhancing the dependability and operational integrity of future urban mobility.