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Candidate architectures for emerging IoV: a survey and comparative study

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Abstract

Intelligent Transportation System (ITS) is observing significant evolution in terms of technology and investment worldwide. This has given birth to the new concept of Internet of vehicles (IoV) as one of the leading applications of the Internet of Things. IoV aims to offer a better sharing of information and communication between vehicles, enabling higher cooperation for common interests. IoV is increasingly attracting the interest of a significant body of research. The e ort was mostly focused on solving various problems encountered in traditional VANETs, such as lack of coordination between vehicles, insufficient information, scalability, etc. Rapidly, IoV observed, particularly interesting advances taking advantage of exponential growth in communication and data analysis technologies. This includes cloud and/or fog computing, large data analytics, machine learning, and artificial intelligence. In this paper, we make a survey of the existing and recently proposed architecture solutions for IoV systems. Moreover, we define a list of criteria, features, and properties associated to the various architectures in order of making critical and insightful comparisons and assessments. Finally, we outline the key future research perspectives on the topic and define the key technical aspects that will help drive the future of IoV architectures.

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References

  1. Atzori L, Lera A, Morabito G (2014) From “smart objects” to “social objects”: The next evolutionary step of the internet of things. IEEE Commun Mag 52(1):97–105

    Article  Google Scholar 

  2. Fortino G, Trun OP (eds) (2014) Internet of things based on smart objects: Technology, middleware and applications. Springer, Berlin

    Google Scholar 

  3. Wan J, Liu J, Shao Z, Vasilakos A, Imran M, Zhou K (2016) Mobile crowd sensing for tra c prediction in internet of vehicles. Sensors 16:88

    Article  Google Scholar 

  4. Contreras-Castillo J, Zeadally S, Guerrero-Ibanez JA (2018) Internet of vehicles: Architecture, protocols, and security. IEEE Internet Things J 5(5):3701–3709

    Article  Google Scholar 

  5. Borcoci E, Obreja S,Vochin, M. (2017) Internet of vehicles functional architectures comparative critical study. In: The 9th international conference on advances in future internet, AFIN, pp 10–14.

  6. Darwish TS, Bakar KA (2018) Fog based intelligent transportation big data analytics in the internet of vehicles environment: motivations, architecture, challenges, and critical issues. IEEE Access 6:15679–15701

    Article  Google Scholar 

  7. Sharma S, Kaushik B (2019) A survey on internet of vehicles: applications, security issues and solutions. VehicCommun 100182:1. https://doi.org/10.1016/j.vehcom.2019.100182

    Article  Google Scholar 

  8. Shen X, Fantacci R, Chen S (2020) Internet of Vehicles [Scanning the Issue]. Proc IEEE 108(2):2

    Article  Google Scholar 

  9. Ji B, Zhang X, Mumtaz S, Han C, Li C, Wen H, Wang D (2020) Survey on the internet of vehicles: network architectures and applications. IEEE Commun Stand Mag 4(1):34–41. https://doi.org/10.1109/mcomstd.001.1900053

    Article  Google Scholar 

  10. Kaiwartya O, Abdullah AH, Cao Y, Altameem A, Prasad M, Lin CT, Liu X (2016) Internet of vehicles: motivation, layered architecture, network model, challenges, and future aspects. IEEE Access 4:5356–5373

    Article  Google Scholar 

  11. Lee EK, Gerla M, Pau G, Lee U, Lim JH (2016) Internet of Vehicles: From intelligent grid to autonomous cars and vehicular fogs. Int J DistribSensNetw 12(9):1

    Google Scholar 

  12. Gross M (2016). A planet with two billion cars. http://www.sciencedirect.com/science/article/pii/S0960982216303414. Accessed 16 Dec 2018.

  13. Huang T (2014) Surveillance video: The biggest big data. Computing Now 7(2):82–91

    Google Scholar 

  14. Chun S, Shin S, Seo S, Eom S, Jung J, Lee KH (2016) A pub/sub- based fog computing architecture for Internet-of-Vehicles. In: IEEE international conference on cloud computing technology and science (CloudCom). IEEE, pp 90–93

  15. Nitti M, Girau R, Floris A, Atzori L (2014). On adding the social dimension to the internet of vehicles: Friendship and middleware. In: IEEE international black sea conference on communications and networking (BlackSeaCom). IEEE, pp 134–138

  16. He X, Ren Z, Shi C, Fang J (2016) A novel load balancing strategy of softwaredened cloud/fog networking in the Internet of Vehicles. China Commun 13(2):140–149

    Article  Google Scholar 

  17. Gartner (2015) Gartner says by 2020, a quarter billion connected vehicles will enable new in-vehicle services and automated driving capabilities. Gartner. https://www.gartner.com/en/newsroom/press-releases/2015-01-26-gartner-says-by-2020a-quarter-billion-connected-vehicleswill-enable-new-in-vehicle-services-and-automateddrivingcapabilities. Accessed 21 January 2019.

  18. Lim J, Jeong YS, Park D-S, Lee H (2016) An efficient distributed mutual exclusion algorithm for intersection trac control. J Supercomput 74(3):1090–1107. https://doi.org/10.1007/s11227-016-1799-3

    Article  Google Scholar 

  19. National Highway Trac Safety Administration (2014) Fact sheet: improving safety and mobility through connected vehicle technology

  20. Feukeu EA, Djouani K, Kurien A (2015) Performance evaluation of the ADSA in a vehicular network: MAC approach in IEEE 802.11 p. J Ambient Intell Hum Comput 6(3):351–360

    Article  Google Scholar 

  21. Hoymann C, Astely D, Stattin M, Wikstrom G, Cheng JF, Hoglund A et al (2016) LTE release 14 outlook. IEEE Commun Mag 54(6):44–49

    Article  Google Scholar 

  22. Tseng YL (2015) LTE-advanced enhancement for vehicular communication. IEEE WirelCommun 22(6):4–7

    Google Scholar 

  23. Buehler R, Pucher J (2017) Trends in walking and cycling safety: recent evidence from high-income countries, with a focus on the United States and Germany. 107(2):281–287

  24. Litman T, Blair R (2017). Managing personal mobility devices (PMDs) on nonmotorized facilities. Victoria Transport Policy Institute

  25. Cai H, Xu B, Jiang L, Vasilakos AV (2017) IoT-based big data storage systems in cloud computing: perspectives and challenges. IEEE Internet Things J 4(1):75–87

    Article  Google Scholar 

  26. Storck CR, Duarte-Figueiredo F (2019) A 5G V2X ecosystem providing internet of vehicles. Sensors 19(3):550

    Article  Google Scholar 

  27. Ge X, Li Z, Li S (2017) 5G software defined vehicular networks. IEEE Commun Mag 55(7):87–93

    Article  Google Scholar 

  28. Stojmenovic I (2014). Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In: Australasian telecommunication networks and applications conference (ATNAC). IEEE, pp 117–122

  29. Wang M, Wu J, Li G, Li J, Li Q, Wang S (2017). Toward mobility support for informationcentric IoV in smart city using fog computing. In: IEEE international conference on smart energy grid engineering (SEGE). IEEE, pp 357–361

  30. Jiacheng C, Haibo ZHOU, Ning Z, Peng Y, Lin G, Xuemin S (2016) Software defined Internet of vehicles: architecture, challenges and solutions. J CommunInf Networks 1(1):14–26

    Google Scholar 

  31. Wang X, Wang C, Zhang J, Zhou M, Jiang C (2017) Improved rule installation for realtime query service in software-de ned internet of vehicles. IEEE Trans IntellTranspSyst 18(2):225–235

    Google Scholar 

  32. Ji X, Yu H, Fan G, Fu W (2016) SDGR: an SDN-based geographic routing protocol for VANET. In: 2016 IEEE international conference on internet of things (iThings) and IEEE green computing and communications (GreenCom) and IEEE cyber, physical and social computing (CPSCom) and IEEE smart data (SmartData). IEEE, pp 276–281

  33. McKeownN AT, Balakrishnan H, Parulkar G, Peterson L, Rexford J, Turner J (2008) OpenFlow: enabling innovation in campus networks. ACM SIGCOMM ComputCommun Rev 38(2):69–74

    Article  Google Scholar 

  34. Liu K, Ng JK, Lee V, Son SH, Stojmenovic I (2016) Cooperative data scheduling in hybrid vehicular ad hoc networks: VANET as a software defined network. IEEE/ACM Trans Netw (TON) 24(3):1759–1773

    Article  Google Scholar 

  35. Mell P, Grance T (2011) The NIST definition of cloud computing

  36. Gunarathne T, Zhang B, Wu TL, Qiu J (2013) Scalable parallel computing on clouds using Twister4Azure iterative MapReduce. Fut Gen ComputSyst 29(4):1035–1048

    Article  Google Scholar 

  37. Park Y, Sur C, Rhee KH (2015) Pseudonymous authentication for secure V2I services in cloud-based vehicular networks. J Ambient Intell Hum Comput 7(5):661–671. https://doi.org/10.1007/s12652-015-0309-4

    Article  Google Scholar 

  38. Gupta M, Sandhu R. (2018). Authorization framework for secure cloud assisted connected cars and vehicular internet of things. In: Proceedings of the 23nd ACM on symposium on access control models and technologies. ACM, 2018. pp. 193–204.

  39. Nahri M, Boulmakoul A, Karim L, Lbath A (2018) IoV distributed architecture for realtimetrac data analytics. ProcediaComputSci 130:480–487

    Google Scholar 

  40. Fan K, Jiang W, Luo Q, Li H, Yang Y (2019). Cloud-based RFID Mutual Authentication Scheme for Efficient Privacy Preserving in IoV. J Frankl Inst

  41. Masip-Bruin X, Marn-Tordera E, Tashakor G, Jukan A, Ren GJ (2016) Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems. IEEE WirelCommun 23(5):120–128

    Google Scholar 

  42. Bonomi F, Milito R, Natarajan P, Zhu J (2014) Fog computing: A platform for internet of things and analytics. Big data and internet of things: A roadmap for smart environments. Springer, Cham, pp 169–186

    Chapter  Google Scholar 

  43. Patel M, Naughton B, Chan C, Sprecher N, Abeta S, Neal A (2014) Mobile-edge computing introductory technical white paper. White Paper, Mobile-edge Computing (MEC) industry initiative, pp 1089–7801

    Google Scholar 

  44. Satyanarayanan M, Bahl P, Caceres R, Davies N (2009) The case for vm-based cloudlets in mobile computing. IEEE PervasComput 4:14–23

    Google Scholar 

  45. Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing. ACM, pp. 13–16.

  46. Yi S, Li C, Li Q (2015) A survey of fog computing: concepts, applications and issues. In Proceedings of the 2015 workshop on mobile big data. ACM, pp 37–42

  47. Tang B, Chen Z, Hefferman G, Pei S, Wei T, He H, Yang Q (2017) Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Trans IndInf 13(5):2140–2150

    Google Scholar 

  48. Negash B, Rahmani AM, Liljeberg P, Jantsch A (2018) Fog computing fundamentals in the internet-of-things. Fog computing in the internet of things. Springer, Cham, pp 3–13

    Chapter  Google Scholar 

  49. Hou X, Li Y, Chen M, Wu D, Jin D, Chen S (2016) Vehicular fog computing: a viewpoint of vehicles as the infrastructures. IEEE Trans VehTechnol 65(6):3860–3873

    Google Scholar 

  50. Jacobson V, Smetters DK, Thornton JD, Plass M, Briggs N, Braynard R (2009). Networking named content. In: Proceedings of the 5th international conference on emerging networking experiments and technologies, CoNEXT, ACM, New York, pp 1–12

  51. Bari MF, Chowdhury SR, Ahmed R, Boutaba R, Mathieu B (2012) A survey of naming and routing in information-centric networks. IEEE Commun Mag 50(12):44–53

    Article  Google Scholar 

  52. Ahlgren B, Dannewitz C, Imbrenda C, Kutscher D, Ohlman B (2012) A survey of information-centric networking. IEEE Commun Mag 50(7):26–36

    Article  Google Scholar 

  53. Gulati A, Aujla GS, Chaudhary R, Kumar N, Obaidat M S (2018). Deep learning-based content centric data dissemination scheme for internet of vehicles. In: IEEE international conference on communications (ICC). IEEE, pp 1–6

  54. Zhang L, Estrin D, Burke J, Jacobson V, Thornton JD, Smetters DK, Papadopoulos C (2010). Named data networking (ndn) project. Relat·orio T·ecnico NDN-0001, Xerox Palo Alto Research Center- PARC, pp 157–158.

  55. Wang X, Wang X (2019) Vehicular content-centric networking framework. IEEE Syst J 13(1):519–529

    Article  Google Scholar 

  56. Li Z, Chen Y, Liu D, Li X (2017) Performance analysis for an enhanced architecture of IoV via content-centric networking. EURASIP J WirelCommunNetw 2017(1):124

    Article  Google Scholar 

  57. Jacobson V, Smetters DK, Thornton JD, Plass M, Briggs N, Braynard R (2009). Networking named content. In: Proceedings of the 5th international conference on emerging networking experiments and technologies, CoNEXT. ACM, New York, pp. 1 12.

  58. Wan J, Zhang D, Zhao S, Yang L, Lloret J (2014) Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions. IEEE Commun Mag 52(8):106–113. https://doi.org/10.1109/mcom.2014.6871677

    Article  Google Scholar 

  59. Nanjie L (2011). Internet of Vehicles your next connection. WinWin Magazine, Issue 11, HUAWEI. OAA. (2016). Open automotive alliance (OAA). Retrieved December 16, 2016, from http://www.openautoalliance.net/#about

  60. Sherazi HHR, Khan ZA, Iqbal R, Rizwan S, Imran MA, Awan K (2019). A heterogeneous IoV architecture for data forwarding in vehicle to infrastructure communication. Mobile Inf Syst

  61. Li B, Li Y (2012) A bi-directional security authentication architecture for the internet of vehicles. Applied Mathematics and Information Sciences, Special Issues, pp 821–827

    Google Scholar 

  62. Yang F, Li J, Lei T, Wang S (2017) Architecture and key technologies for Internet of Vehicles: a survey. J CommunInf Networks 2(2):1–17

    Google Scholar 

  63. Liu K et al (2019) A hierarchical architecture for the future internet of vehicles. IEEE Commun Mag 57(7):41–47

    Article  Google Scholar 

  64. L. Minn et al (2018) Deployment of IoV for smart cities: applications, architecture, and challenges. IEEE Access

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Authors and Affiliations

  1. Physical and Natural Sciences of Tunis, Faculty of Mathematical, University of Tunis El Manar, 2092, Tunis, Tunisia

    Yamina Hichri

  2. Communication Engineering School (Sup’Com), LR11TIC05 MEDIATRON Lab, Faculty of Sciences of Bizerte, University of Carthage, 1083, Tunis, Tunisia

    Soumaya Dahi

  3. Faculty of Sciences of Bizerte, University of Carthage, Tunis, Tunisia

    Habib Fathallah

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  1. Yamina Hichri
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Correspondence to Yamina Hichri.

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Hichri, Y., Dahi, S. & Fathallah, H. Candidate architectures for emerging IoV: a survey and comparative study. Des Autom Embed Syst 25, 237–263 (2021). https://doi.org/10.1007/s10617-021-09249-7

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