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All issues Volume 58 / No 1 (January-February 2024) RAIRO-Oper. Res., 58 1 (2024) 129-149 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 58, Number 1, January-February 2024
Page(s) 129 - 149
DOI https://doi.org/10.1051/ro/2023189
Published online 26 January 2024
  • 5G Americas, Cellular V2X Communications Towards 5G (March 2018). [Google Scholar]
  • M. Ahmed, S. Raza, M.A. Mirza, A. Aziz, M.A. Khan, W.U. Khan, J. Li and Z. Han, A survey on vehicular task offloading: Classification, issues, and challenges. J. King Saud Univ. – Comput. Inf. Sci. 34 (2022) 4135–4162. [Google Scholar]
  • J.G. Andrews, S. Buzzi, W. Choi, S.V. Hanly, A. Lozano, A.C.K. Soong and J.C. Zhang, What will 5G be? IEEE J. Sel. Areas Commun. 32 (2014) 1065–1082. [CrossRef] [Google Scholar]
  • G. Araniti, C. Campolo, M. Condoluci, A. Iera and A. Molinaro, LTE for vehicular networking: a survey. IEEE Commun. Mag. 51 (2013) 148–157. [CrossRef] [Google Scholar]
  • E. Badidi, Z. Mahrez and E. Sabir, Fog computing for smart cities’ big data management and analytics: a review. Future Internet 12 (2020) 190. [CrossRef] [Google Scholar]
  • M.O. Ball, C.J. Colbourn and J.S. Provan, Network reliability. Handb. Oper. Res. Manage. Sci. 7 (1995) 673–762. [Google Scholar]
  • S. Bitam, A. Mellouk and S. Zeadally, VANET-cloud: cloud computing for vehicular ad-hoc networks. IEEE Wireless Commun. 22 (2015) 96–102. [CrossRef] [Google Scholar]
  • F. Bonomi, R. Milito, P. Natarajan and J. Zhu, Fog computing: a platform for internet of things and analytics, in Big Data and Internet of Things: A Roadmap for Smart Environments, edited by N. Bessis and C. Dobre. Springer International Publishing, Cham (2014) 169–186. [CrossRef] [Google Scholar]
  • Cisco White Paper, Visual networking index: forecast and trends, 2017–2022 (February 2019). [Google Scholar]
  • C. Cox, Architecture of the core network, Chapter 2, in An Introduction to 5G. John Wiley & Sons, Ltd. (2021) 29–53. [CrossRef] [Google Scholar]
  • S. Dharmaraja, V. Jindal and U. Varshney, Reliability and survivability analysis for umts networks: an analytical approach. IEEE Trans. Network Serv. Manage. 5 (2008) 132–142. [CrossRef] [Google Scholar]
  • S. Dharmaraja, R. Vinayak and K.S. Trivedi, Reliability and survivability of vehicular ad hoc networks: an analytical approach. Reliab. Eng. Syst. Saf. 153 (2016) 28–38. [CrossRef] [Google Scholar]
  • S. Din, A. Paul, A. Ahmad, S.H. Ahmed, G. Jeon and D.B. Rawat, Hierarchical architecture for 5G based software-defined intelligent transportation system, in IEEE INFOCOM 2018 – IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (2018) 462–467. [Google Scholar]
  • A.M. Farooqi, M.A. Alam, S.I. Hassan and S.M. Idrees, A fog computing model for VANET to reduce latency and delay using 5G network in smart city transportation. Appl. Sci. 12 (2022) 2083. [CrossRef] [Google Scholar]
  • M. Feng, S. Mao and T. Jiang, Base station on-off switching in 5G wireless networks: approaches and challenges. IEEE Wireless Commun. 24 (2017) 46–54. [CrossRef] [Google Scholar]
  • S. Gupta and V. Gupta, Availability analysis of vehicular cloud computing, in Systems Performance Modeling. Vol. 4. Walter de Gruyter, Boston (2021) 21. [Google Scholar]
  • S. Gupta and V. Khaitan Gupta, Reliability and survivability analysis of long-term evolution vehicular ad-hoc networks: an analytical approach. J. Network Syst Manage. 29 (2021) 1–34. [CrossRef] [Google Scholar]
  • P. Hu, S. Dhelim, H. Ning and T. Qiu, Survey on fog computing: architecture, key technologies, applications and open issues. J. Network Comput. App. 98 (2017) 27–42. [CrossRef] [Google Scholar]
  • C. Huang, R. Lu and K.-K.R. Choo, Vehicular fog computing: architecture, use case, and security and forensic challenges. IEEE Commun. Mag. 55 (2017) 105–111. [CrossRef] [Google Scholar]
  • R. Hussain, F. Hussain and S. Zeadally, Integration of VANET and 5G security: a review of design and implementation issues. Future Gener. Comput. Syst. 101 (2019) 843–864. [CrossRef] [Google Scholar]
  • IoT connections forecast – mobility report (December 2022). https://www.ericsson.com/en/reports-and-papers/mobility-report/dataforecasts/iot-connections-outlook. [Google Scholar]
  • I. Kabashkin, Dependability of V2I services in the communication network of the intelligent transport systems, in 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) (2019) 1–6. [Google Scholar]
  • H.A. Khattak, S.U. Islam, I.U. Din and M. Guizani, Integrating fog computing with VANETs: a consumer perspective. IEEE Commun. Stand. Mag. 3 (2019) 19–25. [CrossRef] [Google Scholar]
  • X. Ma, X. Yin and K. Trivedi, On the reliability of safety applications in VANETs. Int. J. Perform. Eng. 8 (2012) 115–130. [Google Scholar]
  • A. Masood, D. Lakew and S. Cho, Security and privacy challenges in connected vehicular cloud computing. IEEE Commun. Surv. Tutorials 22 (2020) 2725–2764. [CrossRef] [Google Scholar]
  • A. Morichetta, V.C. Pujol and S. Dustdar, A roadmap on learning and reasoning for distributed computing continuum ecosystems, 2021 IEEE International Conference on Edge Computing (EDGE) (2021) 25–31. [Google Scholar]
  • M. Petracca, P. Pagano, R. Pelliccia, M. Ghibaudi, C. Salvadori and C. Nastasi, On-board unit hardware and software design for vehicular ad-hoc networks, in Roadside Networks for Vehicular Communications: Architectures, Applications, and Test Fields. IGI Global (2013) 38–56. [CrossRef] [Google Scholar]
  • E. Qafzezi, K. Bylykbashi, P. Ampririt, M. Ikeda, K. Matsuo and L. Barolli, An intelligent approach for cloud-fog-edge computing SDN-VANETs based on fuzzy logic: effect of different parameters on coordination and management of resources. Sensors (Basel) 22 (2022) 878. [CrossRef] [PubMed] [Google Scholar]
  • A.M. Rahmani, S. Bayramov and B. Kiani Kalejahi, Internet of things applications: opportunities and threats. Wireless Pers. Commun. 122 (2022) 451–476. [CrossRef] [PubMed] [Google Scholar]
  • M. Rausand and A. Hoyland, System Reliability Theory: Models, Statistical Methods, and Applications. Vol. 396, John Wiley & Sons (2003). [Google Scholar]
  • M. Rausand and A. Høyland, System Reliability Theory: Models, Statistical Methods and Applications. Wiley-Interscience, Hoboken, NJ (2004). [Google Scholar]
  • T. Reed, INRIX global traffic scorecard (2019). http://inrix.com/scorecard/. [Google Scholar]
  • R.A. Sahner, K. Trivedi and A. Puliafito, Performance and Reliability Analysis of Computer Systems: An Example-Based Approach Using the SHARPE Software Package. Springer Science & Business Media, New York (2012). [Google Scholar]
  • S.A.A. Shah, E. Ahmed, M. Imran and S. Zeadally, 5G for vehicular communications. IEEE Commun. Mag. 56 (2018) 111–117. [CrossRef] [Google Scholar]
  • G. Sharma, Hot redundant versus cold redundant systems. Reliab. Eng. 2 (1981) 193–197. [CrossRef] [Google Scholar]
  • M.S. Sheikh, J. Liang and W. Wang, A survey of security services, attacks, and applications for vehicular ad hoc networks (VANETs). Sensors 19 (2019) 3589. [CrossRef] [PubMed] [Google Scholar]
  • R. Shrestha, R. Bajracharya and S.Y. Nam, Challenges of future VANET and cloud-based approaches. Wireless Commun. Mobile Comput. 2018 (2018) 5603518. [CrossRef] [Google Scholar]
  • A.K. Somani and N.H. Vaidya, Understanding fault tolerance and reliability. Computer 30 (1997) 45–50. [CrossRef] [Google Scholar]
  • M. Songhorabadi, M. Rahimi, A. MoghadamFarid and M. Haghi Kashani, Fog computing approaches in IoT-enabled smart cities. J. Network Comput. App. 211 (2023) 103557. [CrossRef] [Google Scholar]
  • I. Stojmenovic, Fog computing: a cloud to the ground support for smart things and machine-to-machine networks, in 2014 Australasian Telecommunication Networks and Applications Conference (ATNAC). IEEE (2014) 117–122. [Google Scholar]
  • A.B. Tambawal, R.M. Noor, R. Salleh, C. Chembe, M.H. Anisi, O. Michael and J. Lloret, Time division multiple access scheduling strategies for emerging vehicular ad hoc network medium access control protocols: a survey. Telecommun. Syst. 70 (2019) 595–616. [CrossRef] [Google Scholar]
  • R.A. Uzcátegui, A.J. De Sucre and G. Acosta-Marum, Wave: a tutorial. IEEE Commun. Mag. 47 (2009) 126–133. [CrossRef] [Google Scholar]
  • J.S. Weber, M. Neves and T. Ferreto, VANET simulators: an updated review. J. Braz. Comput. Soc. 27 (2021) 8. [CrossRef] [Google Scholar]
  • World Health Organization, High-level meeting of the UN general assembly on global road safety. https://www.who.int/news-room/events/detail/2022/06/30/default-calendar/high-level-meeting-of-the-un-general-assembly-on-global-road-safety. [Google Scholar]
  • L. Yao, J. Wang, X. Wang, A. Chen and Y. Wang, V2X routing in a VANET based on the hidden markov model. IEEE Trans. Intell. Transp. Syst. 19 (2018) 889–899. [CrossRef] [Google Scholar]
  • X. Yin, X. Ma and K.S. Trivedi, MAC and application level performance evaluation of beacon message dissemination in DSRC safety communication. Perform. Eval. 71 (2014) 1–24. [CrossRef] [Google Scholar]
  • F. Zantalis, G. Koulouras, S. Karabetsos and D. Kandris, A review of machine learning and IoT in smart transportation. Future Internet 11 (2019) 94. [CrossRef] [Google Scholar]
  • A. Zekri and W. Jia, Heterogeneous vehicular communications: a comprehensive study. Ad Hoc Networks 75 (2018) 52–79. [CrossRef] [Google Scholar]
  • X. Zhenchang, J. Wu, L. Wu, Y. Chen, J. Yang and P. Yu, A comprehensive survey of the key technologies and challenges surrounding vehicular ad hoc networks. ACM Trans. Intell. Syst. Technol. 12 (2021) 1–30. [Google Scholar]

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