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A novel geographically distributed architecture based on fog technology for improving Vehicular Ad hoc Network (VANET) performance

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Abstract

Intelligent Transportation Systems have gained significant attention among Internet of Things applications due to its specific features and its high capability to promote the innovation of the automotive industries. As part of smart cities, smart mobility initiatives offer new opportunities for intelligent transportation systems to maximize the utilization of the time-sensitive data that are streaming out of different sensory transport resources to support “newcasting” instead of “forecasting” technique. As a result, efficient information dissemination has become the new production factor, notably in terms of mitigating traffic congestion, maximizing bandwidth utilization, and reducing transmission power consumption over the network. Cloud Computing and its counterparts have been established as relatively stable environments for proving a wide number of tackled solutions. However, the limitations of network bandwidth as well as the rapid expansion into the data transfer rate are still the bottlenecks of vehicular networks. The main contribution of this study is to improve Vehicular Ad hoc Network performance in real-time using a geographically distributed computing architecture based on fog technology. This architecture presents a set of novel techniques from different points of view. These novelties include, (i) a flexible registration methodology for improving the navigation process among mobile vehicles; (ii) a generic distributed mechanism to adjust the communication range and the network connectivity; and (iii) a new mathematical model to ensure transmission reliability through establishing powerful communication channels between the vehicular entities and fog layer. The effectiveness of the proposed architecture is evaluated using several performance metrics such as throughput, delay time, and jitter. The experimental results reveal that the worthiness of the proposed architecture to meet the quality of service requirements is more than other state-of-the-art techniques in the literature review.

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References

  1. Atzori L, Iera A, Morabito G (2010) The Internet of Things: A survey. Comput Netw 54(15):2787. https://doi.org/10.1016/j.comnet.2010.05.010

    Article  MATH  Google Scholar 

  2. Ge M, Bangui H, Buhnova B (2018) Big data for internet of things. A Survey, Future Gener Comput Syst

  3. Li Y, Orgerie A, Rodero I, Amersho BL, Parashar M, Menaud JM (2017) End-to-end energy models for Edge Cloud-based IoT platforms: Application to data stream analysis in IoT, Future Gener Comput Syst

  4. Hu P, Dhelim S, Ning H, Qiu T (2017) Survey on fog computing: architecture, key technologies, applications and open issues. J Netw Comput Appl 98:27. https://doi.org/10.1016/j.jnca.2017.09.002

    Article  Google Scholar 

  5. Kai K, Cong W, Tao L (2016) Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues. J China Univ Posts Telecomm 23:56. https://doi.org/10.1016/S1005-8885(16)60021-3

    Article  Google Scholar 

  6. Worldbank. http://documents.worldbank.org/curated/en/446101468324048544/ITS-system-architectures-for-developing-countrieshttp://documents.worldbank.org/curated/en/446101468324048544/ITS-system-architectures-for-developing-countries. Accessed: 2018-12-23

  7. Chen Y, Ardila-Gomez A, Frame G (2017) Achieving energy savings by intelligent transportation systems investments in the context of smart cities. Transp Res D Transpo Environ 54:381. https://doi.org/10.1016/j.trd.2017.06.008

    Article  Google Scholar 

  8. Jain B, Brar G, Malhotra J, Rani S, Ahmed SH (2018) A cross layer protocol for traffic management in Social Internet of Vehicles. Future Gener Comput Syst 82:707. https://doi.org/10.1016/j.future.2017.11.019

    Article  Google Scholar 

  9. Babayo AA, Anisi MH, Ali I (2017) A Review on energy management schemes in energy harvesting wireless sensor networks. Renew Sust Energy Rev 76:1176. https://doi.org/10.1016/j.rser.2017.03.124

    Article  Google Scholar 

  10. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of Things (IoT): A vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645. https://doi.org/10.1016/j.future.2013.01.010

    Article  Google Scholar 

  11. Shaukat U, Ahmed E, Anwar Z, Xia F (2016) Cloudlet deployment in local wireless networks: motivation, architectures, applications, and open challenges. J Netw Comput Appl 62:18

    Article  Google Scholar 

  12. Fernando N, Loke SW, Rahayu W (2013) Mobile cloud computing: a survey. Future Gener Comput Syst 29(1):84

    Article  Google Scholar 

  13. Datta SK, Bonnet C, Haerri J (2015) In Proc. Int. Symp. Consumer Electronics (ISCE), pp 1–2

  14. Zhang P, Zhou M, Fortino G (2018) Security and trust issues in Fog computing. A survey. Future Gener Comput Syst 88:16. https://doi.org/10.1016/j.future.2018.05.008

    Article  Google Scholar 

  15. Jalali F, Hinton K, Ayre R, Alpcan T, Tucker RS (2016) Fog computing May help to save energy in cloud computing. IEEE J Select Areas Comm 34(5):1728. https://doi.org/10.1109/JSAC.2016.2545559

    Article  Google Scholar 

  16. Zhang Y, Niyato D, Wang P (2015) Offloading in mobile cloudlet systems with intermittent connectivity. IEEE Trans Mobile Comput 14(12):2516. https://doi.org/10.1109/TMC.2015.2405539

    Article  Google Scholar 

  17. 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 Veh Technol 65(6):3860

    Article  Google Scholar 

  18. Badawy MM, Ali ZH, Ali HA (2019) Qos provisioning framework for service-oriented internet of things (iot), Cluster Computing, pp 1–17

  19. Boukerche A, Robson E (2018) Vehicular cloud computing: architectures, applications, and mobility, computer networks

  20. Whaiduzzaman M, Sookhak M, Gani A, Buyya R (2014) A survey on vehicular cloud computing. J Netw Comput Appl 40:325

    Article  Google Scholar 

  21. Ghebleh R (2017) A comparative classification of information dissemination approaches in vehicular ad hoc networks from distinctive viewpoints: A survey, Computer Networks

  22. Hurwitz J, Bloor R, Kaufman M, Halper F (2010) Cloud Computing For Dummies. –For dummies Wiley, https://books.google.com.eg/books?id=sTaWAAAAQBAJ

  23. Dinh HT, Lee C, Niyato D, Wang P (2013) A survey of mobile cloud computing: architecture, applications, and approaches. Wirel Comm Mobile Comput 13(18):1587

    Article  Google Scholar 

  24. Yi S, Li C, Li Q (2015) In proceedings of the 2015 workshop on mobile big data ACM, pp 37–42

  25. Ahmed E, Yaqoob I, Gani A, Imran M, Guizani M (2016) Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges. IEEE Wirel Comm 23(5):10

    Article  Google Scholar 

  26. Da Xu L, He W, Li S (2014) Internet of things in industries: a survey. IEEE Trans Ind Inf 10(4):2233

    Article  Google Scholar 

  27. Schleicher JM, Vögler M., Dustdar S, Inzinger C (2016) Application architecture for the internet of cities: Blueprints for future smart city applications. IEEE Internet Comput 20(6): 68

    Article  Google Scholar 

  28. Pereira J, Ricardo L, Luís M., Senna C, Sargento S (2019) Assessing the reliability of fog computing for smart mobility applications in vanets. Future Gener Comput Syst 94:317

    Article  Google Scholar 

  29. Lai Y, Yang F, Su J, Zhou Q, Wang T, Zhang L, Xu Y (2018) Fog-based two-phase event monitoring and data gathering in vehicular sensor networks. Sensors 18(1):82

    Google Scholar 

  30. Datta SK, Bonnet C, Haerri J (2015) In Consumer Electronics (ISCE), 2015 IEEE International Symposium on IEEE, pp 1–2

  31. 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 Veh Technol 65(6):3860

    Article  Google Scholar 

  32. Yan G, Rawat DB (2017) Vehicle-to-vehicle connectivity analysis for vehicular ad-hoc networks. Ad Hoc Networks 58:25

    Article  Google Scholar 

  33. Lai R, Jirachiefpattana A (2012) Communication protocol specification and verification, vol 464. Springer Science & Business Media, New York

    MATH  Google Scholar 

  34. Openfog reference architecture for fog computing. https://www.openfogconsortium.org/, Accessed: 2019-1-27

  35. Cupertino L, Da Costa G, Oleksiak A, Pia W, Pierson JM, Salom J, Siso L, Stolf P, Sun H, Zilio T, et al. (2015) Energy-efficient, thermal-aware modeling and simulation of data centers: the coolemall approach and evaluation results. Ad Hoc Networks 25:535

    Article  Google Scholar 

  36. Ali ZH, Ali HA, Badawy MM (2017) A new proposed the internet of things (iot) virtualization framework based on sensor-as-a-service concept. Wirel Personal Comm 97:1419–1443. https://doi.org/10.1007/s11277-017-4580-x

    Article  Google Scholar 

  37. Graham R, Lubachevsky B, Nurmela K (1998) P. Östergård, Dense packings of congruent circles in a circle. Discrete Mathematics 181:139. https://doi.org/10.1016/S0012-365X(97)00050-2

    Article  MathSciNet  MATH  Google Scholar 

  38. He K, Ye H, Wang Z, Liu J (2018) An efficient quasi-physical quasi-human algorithm for packing equal circles in a circular container. Computers & Operations Research 92:26. https://doi.org/10.1016/j.cor.2017.12.002

    Article  MathSciNet  MATH  Google Scholar 

  39. Serizawa M, Goodman DJ (1993) In IEEE 43rd Vehicular Technology Conference IEEE, pp 528–531

  40. Marzetta TL, Hochwald BM (2006) Fast transfer of channel state information in wireless systems. IEEE Trans. Signal Processing 54(4):1268

    Article  Google Scholar 

  41. Bozorgi SM, Rostami AS, Hosseinabadi AAR, Balas VE (2017) A new clustering protocol for energy harvesting-wireless sensor networks. Comput Electr Eng 64:233. https://doi.org/10.1016/j.compeleceng.2017.08.022

    Article  Google Scholar 

  42. Wen S, Huang C, Chen X, Ma J, Xiong N, Li Z (2018) Energy-efficient and delay-aware distributed routing with cooperative transmission for internet of things. J Parallel Distr Comput 118:46. https://doi.org/10.1016/j.jpdc.2017.08.002

    Article  Google Scholar 

  43. Cong Y, Zhou X, Kennedy RA (2015) Interference Prediction in Mobile Ad Hoc Networks With a General Mobility Model. IEEE Trans Wirel Commun 14(8):4277. https://doi.org/10.1109/TWC.2015.2418763

    Article  Google Scholar 

  44. Ameixieira C, Cardote A, Neves F, Meireles R, Sargento S, Coelho L, Afonso J, Areias B, Mota E, Costa R, et al. (2014) Harbornet: a real-world testbed for vehicular networks. IEEE Communications magazine 52(9):108

    Article  Google Scholar 

  45. Alahmadi AA, Lawey AQ, El-Gorashi TE, Elmirghani JM (2017) In Network of the Future (NOF), 2017 8th International Conference on th, IEEE, pp 22–26

  46. Osman RA, Peng XH, Omar M (2018) Adaptive cooperative communications for enhancing qos in vehicular networks, Physical Communication

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Correspondence to Zainab H. Ali.

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Ali, Z.H., Badawy, M.M. & Ali, H.A. A novel geographically distributed architecture based on fog technology for improving Vehicular Ad hoc Network (VANET) performance. Peer-to-Peer Netw. Appl. 13, 1539–1566 (2020). https://doi.org/10.1007/s12083-020-00910-9

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