Classification, Challenges and Critical Comparison of Proposed Solutions for Vehicular Clouds

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Hassan Mistareehi
D. Manivannan

Abstract

Modern vehicles are equipped with devices that have computation, storage, communication and sensing capabilities. Vehicles can share the information collected with other vehicles and also can share this information with an external cloud. Vehicles can also form a cloud among themselves and use their underutilized resources to process and share the information collected by various vehicles. In this paper, we present a critical comparison and classification of vehicular cloud architectures proposed in the literature. We also explore the challenges, proposed solutions for meeting the challenges and their drawbacks in implementing vehicular cloud and identify some open issues that need to be addressed for the successful implementation of vehicular clouds.

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How to Cite
Hassan Mistareehi, & D. Manivannan. (2019). Classification, Challenges and Critical Comparison of Proposed Solutions for Vehicular Clouds. International Journal of Next-Generation Computing, 10(1), 01–18. https://doi.org/10.47164/ijngc.v10i1.156

References

  1. Abid, H., Phuong, L. T., Wang, J., Lee, S., and Qaisar, S. 2011. V-cloud: vehicular cyber-physical systems and cloud computing. In Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies. ACM, ACM, 1-5.
  2. Al-Sultan, S., Al-Bayatti, A., and Zedan, H. 2013. Context-aware driver behavior detection system in intelligent transportation systems. IEEE Transactions on Vehicular Technology 62, 9 (November), 4264-4275.
  3. Arkian, H., Atani, R., Diyanat, A., and Pourkhalili, A. 2015. A cluster-based vehicular cloud architecture with learning-based resource management. The Journal of Supercomputing 71, 4 (April), 1401-1426.
  4. Bernsen, J. and Manivannan, D. 2008. Greedy routing protocols for vehicular ad hoc networks. In Proceedings of Wireless Communications and Mobile Computing Conference.
  5. Bitam, S., Mellouk, A., and Zeadally, S. 2015. VANET-CLOUD: A generic cloud computing model for vehicular ad hoc networks. IEEE Wireless Communications 22, 1 (February),96-102.
  6. Bravo-Torres, J., Ordonez-Morales, E., Lopez-Nores, M., Blanco-Fernandez, Y., and Pazos-Arias, J. 2014. Virtualization in VANETs to support the vehicular cloud experiments with the network as a service model. In IEEE Proceedings of Third International Conference on Future Generation Communication Technology. IEEE, 1-6.
  7. Chaqfeh, M., Mohamed, N., Jawhar, I., and Wu, J. 2016. Vehicular cloud data collection for intelligent transportation systems. In Proceedings of IEEE Smart Cloud Networks and Systems. IEEE, 1-6.
  8. Eltoweissy, M., Olariu, S., and Younis, M. 2011. Towards autonomous vehicular clouds. EAI Endorsed Transactions on Mobile Communications and Applications 1, 1 (September), 1-11.
  9. Hussain, R. and Oh, H. 2014. Cooperation-aware vanet clouds: Providing secure cloud services to vehicular ad hoc networks. Journal of Information Processing Systems 10, 1, 103-118.
  10. Hussain, R., Son, J., Eun, H., Kim, S., and Oh, H. 2012. Rethinking vehicular communications: merging VANET with cloud computing. In Proceedings of the 4th International Conference on Cloud Computing Technology and Science. IEEE, IEEE, 606-609.
  11. Kong, Q., Lu, R., Zhu, H., Alamer, A., and Lin, X. 2016. A secure and privacy-preserving incentive framework for vehicular cloud on the road. In Proceedings of Global Communications Conference (GLOBECOM). IEEE, 1-6.
  12. Kumar, S., Gollakota, S., and Katabi, D. 2012. A cloud-assisted design for autonomous driving. In Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing. ACM, 41-46.
  13. Lee, E., Lee, E.-K., Gerla, M., and Oh, S. Y. 2014. Vehicular cloud networking: architecture and design principles. IEEE Communications Magazine 52, 2 (February), 148-155.
  14. Lim, K., Abumuhfouz, I., and Manivannan, D. 2015. Secure incentive-based architecture for vehicular cloud. Springer Lecture Notes in Computer Science 9143, 361-374.
  15. Lim, K. and Manivannan, D. 2016. An efficient protocol for authenticated and secure message
  16. delivery in vehicular ad hoc networks. Vehicular Communications 4, 30-37.
  17. Lin, X., Sun, X., Ho, P.-H., and Shen, X. 2007. GSIS: A secure and privacy-preservingprotocol for vehicular communications. IEEE Transactions on Vehicular Technology 56, 6(November), 3442-3456.
  18. M. Salahuddin, A. A.-F. and Guizani, M. 2015. Software-defined networking for RSU clouds in support of the internet of vehicles. IEEE Internet of Things Journal 2, 2 (April), 133-144.
  19. Mekki, T., Jabri, I., Rachedi, A., and ben Jemaa, M. 2017. Vehicular cloud networks: Challenges, architectures, and future directions. Vehicular Communications 9, 268-280.
  20. Olariu, S., Khalil, I., and Abuelela, M. 2011. Taking VANET to the clouds. International Journal of Pervasive Computing and Communications 7, 1 (February), 7-21.
  21. Qin, Y., Huang, D., and Zhang, X. 2012. Vehicloud: Cloud computing facilitating routing in vehicular networks. In Proceedings of IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 1438-1445.
  22. Raya, M., Papadimitratos, P., and Hubaux, J. 2006. Securing vehicular communications. IEEE Wireless Communications 13, 5 (October), 8-15.
  23. Samara, G., Al-Salihy, W., and Sures, R. 2010. Security analysis of vehicular ad hoc networks. In Proceedings of Network Applications Protocols and Services. IEEE, 55-60.
  24. Sharma, M., Bali, R., and Kaur, A. 2015. Dynamic key based authentication scheme for Vehicular Cloud Computing. In Proceedings of 2015 International Conference on Green Computing and Internet of Things. IEEE, 1059-1064.
  25. T. Refaat, B. K. and Mouftah, H. 2014. Dynamic virtual machine migration in a vehicular cloud. In Proceedings of IEEE Symposium on Computers and Communication (ISCC). 1-6.
  26. Toutain, F., Bouabdallah, A., and Zemek, R. 2011. Interpersonal context-aware communication services. IEEE Communications Magazine 49, 1 (January), 68-74.
  27. Wan, J., Zhang, D., Zhao, S., Yang, L., and Lloret, J. 2014. Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions. IEEE Communications Magazine 52, 8 (August), 106-113.
  28. Wang, J., Cho, J., Lee, S., and Ma, T. 2011. Real time services for future cloud computing enabled vehicle networks. In Proceedings of International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 1-5.
  29. Whaiduzzaman, M., Sookhak, M., Gani, A., and Buyya, R. 2014. A survey on vehicular cloud computing. Journal of Network and Computer Applications 40, 325-344.
  30. Xu, K., Wang, K., Amin, R., Martin, J., and Izard, R. 2015. A fast cloud-based network selection scheme using coalition formation games in vehicular networks. IEEE Transactions on Vehicular Technology 64, 11 (November), 5327-5339.
  31. Yan, G., Wen, D., S.Olariu, and M.Weigle. 2013. Security challenges in vehicular cloud computing. IEEE Transactions on Intelligent Transportation Systems 14, 1 (March), 284- 294.
  32. Yu, R., Zhang, Y., Gjessing, S., Xia, W., and Yang, K. 2013. Toward cloud-based vehicular networks with efficient resource management. IEEE Network 27, 5 (October), 48-55.