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Resource Management in SDN-VANETs: Coordination of Cloud-Fog-Edge Resources Using Fuzzy Logic

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Advances in Internet, Data and Web Technologies (EIDWT 2020)

Abstract

In this work, we propose an intelligent system for coordination and management of the cloud-fog-edge resources in Vehicular Ad hoc Networks (VANETs) using Software Defined Networking (SDN) and Fuzzy Logic (FL) approaches. The proposed system called Fuzzy-based System for Resource Management (FSRM) determines the appropriate resources to be used by a vehicle to process different VANETs applications. The decision is made by prioritizing the application requirements: Time Sensitivity (TS) and Data Size (DS), and by considering the available connections of the vehicle i.e., Number of Neighboring Vehicles (NNV) and Vehicle Relative Speed with Neighboring Vehicles (VRSNV). We demonstrate in simulation the feasibility of FSRM to improve the management of the network resources.

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References

  1. Boukerche, A., Robson, E.: Vehicular cloud computing: architectures, applications, and mobility. Comput. Netw. 135, 171–189 (2018)

    Article  Google Scholar 

  2. Bylykbashi, K., Liu, Y., Matsuo, K., Ikeda, M., Barolli, L., Takizawa, M.: A fuzzy-based system for cloud-fog-edge selection in VANETs. In: International Conference on Emerging Internetworking, Data & Web Technologies, pp. 1–12. Springer (2019)

    Google Scholar 

  3. Cuka, M., Elmazi, D., Ikeda, M., Matsuo, K., Barolli, L.: IoT node selection in opportunistic networks: implementation of fuzzy-based simulation systems and testbed. Internet Things 8, 100105 (2019)

    Article  Google Scholar 

  4. Hu, Y.C., Patel, M., Sabella, D., Sprecher, N., Young, V.: Mobile edge computing-a key technology towards 5G. ETSI White Paper, vol. 11, no. 11, pp. 1–16 (2015)

    Google Scholar 

  5. Hussain, R., Son, J., Eun, H., Kim, S., Oh, H.: Rethinking vehicular communications: merging VANET with cloud computing. In: 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings, pp. 606–609 (2012)

    Google Scholar 

  6. Kandel, A.: Fuzzy Expert Systems. CRC Press, Inc., Boca Raton (1992)

    Google Scholar 

  7. Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty, and Information. Prentice Hall, Upper Saddle River (1988)

    MATH  Google Scholar 

  8. Ku, I., Lu, Y., Gerla, M., Gomes, R.L., Ongaro, F., Cerqueira, E.: Towards software-defined VANET: architecture and services. In: 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET), pp. 103–110 (2014)

    Google Scholar 

  9. Matsuo, K., Cuka, M., Inaba, T., Oda, T., Barolli, L., Barolli, A.: Performance analysis of two WMN architectures by WMN-GA simulation system considering different distributions and transmission rates. Int. J. Grid Util. Comput. 9(1), 75–82 (2018)

    Article  Google Scholar 

  10. McNeill, F.M., Thro, E.: Fuzzy Logic: A Practical Approach. Academic Press Professional, Inc., San Diego (1994)

    MATH  Google Scholar 

  11. Munakata, T., Jani, Y.: Fuzzy systems: an overview. Commun. ACM 37(3), 69–77 (1994)

    Google Scholar 

  12. Olariu, S., Hristov, T., Yan, G.: The next paradigm shift: from vehicular networks to vehicular clouds. Mob. Ad Hoc Netw. Cut. Edge Dir. 56(6), 645–700 (2013)

    Article  Google Scholar 

  13. Olariu, S., Khalil, I., Abuelela, M.: Taking vanet to the clouds. Int. J. Pervasive Comput. Commun. 7(1), 7–21 (2011)

    Article  Google Scholar 

  14. Ozera, K., Bylykbashi, K., Liu, Y., Barolli, L.: A fuzzy-based approach for cluster management in vanets: performance evaluation for two fuzzy-based systems. Internet Things 3, 120–133 (2018)

    Article  Google Scholar 

  15. Ozera, K., Inaba, T., Bylykbashi, K., Sakamoto, S., Ikeda, M., Barolli, L.: A wlan triage testbed based on fuzzy logic and its performance evaluation for different number of clients and throughput parameter. Int. J. Grid Util. Comput. 10(2), 168–178 (2019)

    Article  Google Scholar 

  16. Qafzezi, E., Bylykbashi, K., Spaho, E., Barolli, L.: An intelligent approach for resource management in SDN-VANETs using fuzzy logic. In: International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 747–756. Springer (2019)

    Google Scholar 

  17. Qafzezi, E., Bylykbashi, K., Spaho, E., Barolli, L.: A new fuzzy-based resource management system for SDN-VANETs. Int. J. Mob. Comput. Multimed. Commun. (IJMCMC) 10(4), 1–12 (2019)

    Article  Google Scholar 

  18. Stojmenovic, I., Wen, S., Huang, X., Luan, H.: An overview of fog computing and its security issues. Concurr. Comput. Pract. Exp. 28(10), 2991–3005 (2016)

    Article  Google Scholar 

  19. Truong, N.B., Lee, G.M., Ghamri-Doudane, Y.: Software defined networking-based vehicular adhoc network with fog computing. In: 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 1202–1207 (2015)

    Google Scholar 

  20. Xu, W., Zhou, H., Cheng, N., Lyu, F., Shi, W., Chen, J., Shen, X.: Internet of vehicles in big data era. IEEE/CAA J. Autom. Sin. 5(1), 19–35 (2018)

    Article  Google Scholar 

  21. Yuan, Q., Zhou, H., Li, J., Liu, Z., Yang, F., Shen, X.S.: Toward efficient content delivery for automated driving services: an edge computing solution. IEEE Netw. 32(1), 80–86 (2018)

    Article  Google Scholar 

  22. Zadeh, L.A., Kacprzyk, J.: Fuzzy Logic for the Management of Uncertainty. Wiley, New York (1992)

    Google Scholar 

  23. Zimmermann, H.J.: Fuzzy control. In: Fuzzy Set Theory and Its Applications, pp. 203–240. Springer (1996)

    Google Scholar 

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Correspondence to Ermioni Qafzezi .

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Qafzezi, E., Bylykbashi, K., Ishida, T., Matsuo, K., Barolli, L., Takizawa, M. (2020). Resource Management in SDN-VANETs: Coordination of Cloud-Fog-Edge Resources Using Fuzzy Logic. In: Barolli, L., Okada, Y., Amato, F. (eds) Advances in Internet, Data and Web Technologies. EIDWT 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-030-39746-3_13

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