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Efficient Protected VNF Placement and MEC Location Selection for Dynamic Service Provisioning in 5G Networks

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Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference (DCAI 2023)

Abstract

Multi-Access Edge Computing (MEC) and Network Function Virtualization (NFV) have emerged as promising technologies for providing low-latency and high-bandwidth services to mobile users through Service Function Chains (SFCs) consisting of Virtual Network Functions (VNFs). However, the efficient utilization of network resources and optimal placement of MECs to host VNFs remain challenging issues in NFV-based dynamic networks. Since the proximity of MEC nodes to end-users and the availability of resources at the location impact the blocking ratio in VNF placement, in this paper we analyze the impact of the location of the set of MEC resources in the network. Thus, starting from the work previously done related to the VNF placement scheme with different protection methods to accommodate services in MEC nodes, we conduct a simulation to evaluate the impact of different MEC locations on the blocking ratio. Our results demonstrate that strategic placement of MEC locations can significantly reduce the blocking ratio.

This work is part of IoTalentum project that has received funding from the EU H2020 research and innovation programme under the MSCA grant agreement No 953442. It is also supported by Consejería de Educación de la Junta de Castilla y León and the European Regional Development Fund (Grant VA231P20), and the Spanish Ministry of Science of Innovation and the State Research Agency (Grant PID2020-112675RB-C42 funded by MCIN/AEI/10.13039/501100011033).

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Correspondence to Maryam Masoumi .

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Masoumi, M. et al. (2023). Efficient Protected VNF Placement and MEC Location Selection for Dynamic Service Provisioning in 5G Networks. In: Mehmood, R., et al. Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems, vol 741. Springer, Cham. https://doi.org/10.1007/978-3-031-38318-2_44

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