ABSTRACT
The fog computing-based radio access networks work at the same time as capable worldview commencing to 5G remote transmitting framework give elevated unearthly along with vitality effectiveness. In center thought obtain complete points to interest of neighborhood radio flag preparing, consistent on radio asset administration and disseminated putting away abilities in edge gadgets, which can diminish the substantial weight on front haul. In light of fog computing, the cooperation radio flag handling (CRSP) cannot exclusively accomplish during the unified baseband unit into cloud radio access networks. Unfasten concern into the condition of software defined networking, network function virtualization and edge caching recognized. This paper attempts to minimize the security issues in the performance of edge cashing by using Markov chain model. Simulation results are able to reduce the bandwidth consumption of F_RAN through edge caching in between remote radio heads and user equipment's.
- Abreu, D. Velasquez, K. Curado and M. Monteiro. 2017. A resilient Internet of Things architecture for smart cities. Ann. Telecommun. 19--30.Google Scholar
- Airvana, H. Hawilo, A. Shami, M. Mirahmadi, and R. Asal. 2014. NFV: State of the art, challenges and implementation in next generation mobile networks (vEPC). IEEE Network. 28(6):18--26.Google ScholarCross Ref
- Arkian, Zhang and Chiang. 2017. Fog and IoTAn Overview of Research Opportunities. IEEE Internet of Things Journal.Google Scholar
- Barbosa, J. Li, M. Peng, A. Cheng, and C. Wang. 2014. Resource allocation optimization for delay-Sensitive traffic in fronthaul constrained cloud radio access networks. to appear in IEEE Systems Journal.Google Scholar
- Beck, S. Woo, E. Jeong, S. Park, J. Lee, S. Ihm, and K. Park. 2016. Comparison of caching strategies in modern cellular backhaul networks in Proc. ACM MobiSys. 319--332. Google ScholarDigital Library
- Bonomi, F.Milito, R. Zhu, and Addepalli. 2016. Fog Computing and its Role in the Internet of Things. 13--16. Google ScholarDigital Library
- Fan.J, J. Chen, Y. Du, W. Gao, J. Wu, and Y. Sun. 2013. Geocommunity- based broadcasting for data dissemination in mobile social networks. IEEE Trans. 24(4): 734--743. Google ScholarDigital Library
- Ivan, M. Zhang, Y. Duan, H. Yun and Z. Zhao. 2013. Semantics-Aware Android Malware Classification Using Weighted Contextual API Dependency Graphs, Proceedings of the ACM SIGSAC. Conference on Computer and Communications Security.1105--1116. Google ScholarDigital Library
- Peng. M, C.Wang, H.Xiang, J.Li and V.Lau. 2015. Recent Advances in Underlay Heterogeneous Networks: Interference Control Resource Allocation and Self-Srganization. IEEE Communication.Sur. Tut.17 (2):700--729.Google ScholarCross Ref
- Shanhe and Riman. 2014. Towards programmable enterprise wlans with Odin in Proceedings of the first workshop on Hot topics in software defined networks. IEEE Commun.Google Scholar
- Sawati and Zui. 2015. Software Defined Networking-based Vehicular Adhoc Network with Fog Computing. IFIP/IEEE symposium on interated Network Managment.15--20.Google Scholar
- Truong.N, G. Lee, and Y. Ghamri-Doudane. 2015. Software Defined Networking-based Vehicular Adhoc Network with Fog Computing. IFIP/IEEE symposium on interated Network Managment. 15--20.Google Scholar
- Sun. X, N. Ansari and Q. Fan. 2015. Green Energy Aware Avatar Migration Strategy in Green Cloudlet Networks. IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom). 139--146. Google ScholarDigital Library
- Bonomi.F, J.Zhu, R.Milito and S.Addepalli. 2012. Fog Computing and Its Role in the Internet of Things. In Workshop on Mobile Cloud Computing, MCC'12, Helsinki, Finland. 13--16. Google ScholarDigital Library
- Brito, M. Hoque, S.Magedanz, T. Steinke, R. Willner, A. Nehls, D. Keils and O. Schreiner.2017. A service orchestration architecture for fog-enabled infrastructures. In Proceedings of the Second International Conference on fog and Mobile Edge Computing (FMEC). 127--132.Google Scholar
- Brogi, Arkian, H. Reza, Diyanat and A. Pourkhalili. 2017. Fog-based data analytics scheme with cost-efficient resource provisioning for IoTcrowdsensing applications. Journal of Network and Computer Applications. 152--165.Google Scholar
- Cheng.A, C.Wang, J.Li and M.Peng. 2012. Resource Allocation Optimization for Delay-Sensitive Traffic in Fronthaul Constrained Cloud Radio Access Networks. IEEE Systems Journal.Google Scholar
- Chiang, and M. Zhang. 2016. Fog and IoT An overview of research opportunities.IEEE Internet Things.854--864.Google Scholar
- Dragoni.D, N. Giallorenzo, S. Lafuente, A. Mazzara, M. Montesi, F. Mustafin, R. Safina and L. Microservices. 2017. In Present and Ulterior Software Engineering Springer: Cham, Switzerland. 195--216.Google Scholar
- Fan.J, J. Chen, Y. Du, W. Gao, J. Wu, and Y. Sun. 2013. Geocommunity- based broadcasting for data dissemination in mobile social networks. IEEE Trans. 24(4): 734--743. Google ScholarDigital Library
- Ziu.j.2015. Software defined and virtualized wireless access in future wireless networks: scenarios and standards. IEEE Commun. 50(6): 25--34.Google Scholar
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