Name
Abstract | ||
|---|---|---|
The inclusion of Network Function Virtualization (NFV) and Software-Defined Networking in next-generation communication networks (e.g., 5G and beyond) influence Telecommunication Service Providers (TSPs) to deploy Virtual Network Functions (VNFs) to improve network performance without in-curring additional usage of network resources. The softwarization and virtualization of network resources uplift the Network Slicing (NS) concept to optimally place the VNF instances over Service Function Chains (SFCs) for superior service delivery. Limited network capacity and storage work as a major hindrance toward better Quality-of-Service (QoS), so optimal VNF embedding over SFCs becomes an obligatory aspect. In this work, we have studied the VNF embedding problem (VNF-EP) over SFC instances for Softwarized 5G Networks. We have proposed a novel approach for dynamic VNF sharing over multiple SFCs, considering the flow requests of SFC for individual Network Slice. The inter-slice co-ordinations are done considering the common service requests among independent and heterogeneous Slices. The mathematical formulation follows a MILP based optimization approach that optimally controls the VNF sharing to increase network efficiency and hardware usage. This flexible and shareable VNF embedding approach (FlexShare-VNF) results in significant energy-efficient service delivery in a low latency environment, and our performance evaluation also supports the claim. This approach will be extremely helpful for smooth network up-gradation in resource-restricted environments for future network advancements. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/NCC55593.2022.9806465 | 2022 National Conference on Communications (NCC) |
Keywords | DocType | ISBN |
SDN,NFV,5G,VNF,SFC,TSPs,Energy effi-ciency,MILP,VNF embedding | Conference | 978-1-6654-5137-6 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Deborsi Basu | 1 | 2 | 2.06 |
| Abhishek Jain | 2 | 0 | 0.34 |
| Uttam Ghosh | 3 | 0 | 0.68 |
| Raja Datta | 4 | 212 | 22.65 |