Modelling the Admission Ratio in NFV-Based Converged Optical-Wireless 5G Networks

• Published in: IEEE transactions on vehicular technology Vol. 70; no. 11; pp. 12024 - 12038
• Main Authors: Mosahebfard, Mohammadreza, Vardakas, John S., Verikoukis, Christos
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; admission ratio; Algorithms; Analytical model; Analytical models; Complexity; Convergence; Model accuracy; Network function virtualization; network slicing; Occupancy; Optical communication; Optimization; Passive optical networks; Resource management; Servers; Virtual networks; Wireless networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2021.3113838

Network Function Virtualization (NFV)-based 5G networks deliver specific services to a end-users through the creation of Service Function Chains (SFCs), which are composed of a number of Virtualized Network Functions (VNFs) interconnected via a set of virtual links (vLinks). VNFs consume computational resources of the network's servers, while vLinks utilize the communicational resources of the network. The efficient utilization of network resources remains a challenge in NFV-based networks. To this end, in this paper, we propose an analytical framework for the Admission Ratio (AR) calculation in NFV-based converged optical-wireless 5G networks. The proposed methodology employs a network slicing architecture in which different network slices form end-to-end logically isolated networks and each slice delivers a specific service type to the users through its SFC(s). In the proposed analysis, we not only take into account the occupancy distribution in both the network's computational and communicational domains (servers and fiber links), but we also consider the SFC establishment AR by taking into account different sub-service-classes belonging to different slices. The accuracy of the model is evaluated through the comparison of analytical and simulation results and was found satisfactory. Furthermore, the proposed model is employed for the determination of the optimal (minimum) capacity for all SFCs elements (VNFs and vLinks), in a way that users belonging to a specific slice experience a predefined value of AR as minimum. Additionally, our calculations deploy recursive formulas, which have a low computational complexity, as opposed to time-consuming simulations, without requiring the application of complex optimization algorithms.