Abstract
Future networks starting from 5G will depend on network slicing to meet a wide range of network services (NSs) with various quality of service (QoS) requirements. With the powerful Network Function Virtualization (NFV) technology available, network slices can be rapidly deployed and centrally managed, giving rise to simplified management, high resource utilization, and cost-efficiency. This is achieved by realizing NSs on general-purpose hardware, hence, replacing traditional middleboxes. However, realizing fast deployment of end-to-end network slices still requires intelligent resource allocation algorithms to efficiently use the network resources and ensure QoS among different slice categories during congestion cases. This is especially important at the links of the network because of the scarcity of their resources. Consequently, this paper proposes a paradigm based on NFV architecture aimed at providing the massive computational capacity required in the NSs and supporting the resource allocation strategy proposed for multiple slice networks based on resources utilization optimization using a proposed and analyzed Squatting-Kicking model (SKM). SKM is a suitable algorithm for dynamically allocating network resources to different priority slices along paths and improving resource utilization under congested scenarios. Simulation results show that the proposed service deployment algorithm achieves 100% in terms of both overall resource utilization and admission for higher priority slices in some scenarios in bandwidth-constrained contexts, which cannot be achieved by other existing schemes due to priority constraints.
Highlights
I N network slicing of future networks starting from 5G, the intent is to take infrastructure resources from the spectrum, antennas and all of the backend network and devices and use them to realize multiple sub-networks with different properties
- 6c, the Maximum Allocation Model (MAM) behavior in which there are no preemptions limits the link utilization to 491.35 Mbps on average for the entire simulation window. This results from the fact that, in the simulation, the U(T) most of the time is below the 622 Mbps link capability even when CT1, CT2 and CT3 are congested
1) Results Evaluation Figs. 10- 11 show the results of each algorithm in terms of U, acceptance ratio (AR), utilization per slice (Uc), acceptance ratio per slice (ARc), Pre, LB and Lov using different traffic load according to experiments 1–3
Summary
I N network slicing of future networks starting from 5G, the intent is to take infrastructure resources from the spectrum, antennas and all of the backend network and devices and use them to realize multiple sub-networks with different properties. Virtualization and progressive softwarization of network function in NFV architecture give rise to new opportunities for improving application tools and platforms in the market, like management and orchestration (MANO), for controlling the life-cycles of the slices and as well as the underlying VNFs at the network levels; for instance, European Telecommunications Standards Institute (ETSI) standardizes the VNF structure [11] and suggests the OpenSource MANO (OSM) [12] platform These platforms can undoubtedly facilitate the sharing of resources between slices, but they still require intelligent resource allocation algorithms to permit a particularised slice to meet its service level agreement (SLA) such as QoS and bandwidth.
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