Abstract
Network technologies are dealing with a massive urge to breakthrough the fundamental endorsements of networks. Software-Defined Networking (SDN) is taking the lead in cloud Data Centers (DCs) to ensure the resource management of many policy adaptations, regarding the performance of Network Virtualization (NV) that must find the appropriate hardware components to map either a Virtual Machine (VM) or a virtual link, which resume the general concept of Virtual Network Embedding (VNE). In this paper, a Grey Wolf Optimizer (GWO) is represented as an intelligent approach for solving the VNE problem in the cloud with SDN consolidation. It is a recent meta-heuristic with low complex processing. Our implementation is based on CloudSimSDN that is an extension from the CloudSim simulation tool. The results indicate that maximizing the utilization of localhost resources maintain a considerable amount of energy consumption and consequently will provide better policy management for physical DCs.
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SDN-definition. https://www.opennetworking.org/sdn-definition. Accessed 23 June 2019
Fischer, A., Botero, J.F., Beck, M.T., De Meer, H., Hesselbach, X.: Virtual network embedding: a survey. IEEE Commun. Surv. Tutor. 15(4), 1888–1906 (2013)
Mijumbi, R., Serrat, J., Rubio-Loyola, J., Bouten, N., De Turck, F., Latré, S.: Dynamic resource management in SDN-based virtualized networks. In: 10th International Conference on Network and Service Management (CNSM) and Workshop, pp. 412–417. IEEE, Brazil (2014)
Dehury, C.K., Sahoo, P.K.: DYVINE: fitness-based dynamic virtual network embedding in cloud computing. IEEE J. Sel. Areas Commun. 37, 1029–1045 (2019)
Al-Moalmi, A., Luo, J., Salah, A., Li, K.: Optimal virtual machine placement based on grey wolf optimization. Electronics 8(3), 283 (2019)
Calheiros, R., Ranjan, R., Beloglazov, A., De Rose, C., Buyya, R.: CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw.-Pract. Exp. 41, 23–50 (2011)
Shahbazi, H., Sepideh, J.N.: Smart deployment of virtual machines to reduce energy consumption of cloud computing based data centers using gray wolf optimizer. In: International Conference on Information and Software Technologies, pp. 164–177. Springer, Cham (2018)
Nasiri, A.A., Derakhshan, F.: Assignment of virtual networks to substrate network for software defined networks. Int. J. Cloud Appl. Comput. (IJCAC) 8(4), 29–48 (2018)
Yao, X., Wang, H., Gao, C., Yi, S.: Maximizing network utilization for SDN based on Particle Swarm Optimization. In: IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 921–925. IEEE, USA (2016)
McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., Turner, J.: OpenFlow: enabling innovation in campus networks. ACM SIGCOMM Comput. Commun. Rev. 38(2), 69–74 (2008)
Azodolmolky, S., Wieder, P., Yahyapour, R.: SDN-based cloud computing network- ing. In: 15th International Conference on Transparent Optical Networks (ICTON), pp. 1–4. IEEE, Spain (2013)
Son, J., Buyya, R.: A taxonomy of software-defined networking (SDN)-enabled cloud computing. ACM Comput. Surv. (CSUR) 51(3), 59 (2018)
Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)
Al-Fares, M., Loukissas, A., Vahdat, A.: A scalable, commodity data center network architecture. In: ACM SIGCOMM Computer Communication Review, vol. 38, no. 4, pp. 63–74, USA (2008)
Saremi, S., Mirjalili, S.Z., Mirjalili, S.M.: Evolutionary population dynamics and grey wolf optimizer. Neural Comput. Appl. 26(5), 1257–1263 (2015)
Son, J., Dastjerdi, A.V., Calheiros, R.N., Ji, X., Yoon, Y., Buyya, R.: CloudSimSDN: modeling and simulation of software-defined cloud data centers. In: 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 475–484. IEEE, China (2015)
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Bouchair, A., Makhlouf, S.A., Belabbas, Y. (2020). Grey Wolf Optimizer for Virtual Network Embedding in SDN-Enabled Cloud Environment. In: Serrhini, M., Silva, C., Aljahdali, S. (eds) Innovation in Information Systems and Technologies to Support Learning Research. EMENA-ISTL 2019. Learning and Analytics in Intelligent Systems, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-030-36778-7_35
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DOI: https://doi.org/10.1007/978-3-030-36778-7_35
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