Journal article Open Access

Online VNF Lifecycle Management in a MEC-enabled 5G IoT Architecture

Sarrigiannis, Ioannis; Ramantas, Kostas; Kartsakli, Elli; Mekikis, Prodromos-Vasileios; Antonopoulos, Angelos; Verikoukis, Christos

The upcoming fifth generation (5G) mobile communications urge software-defined networks (SDNs) and network function virtualization (NFV) to join forces with the multiaccess edge computing (MEC) cause. Thus, reduced latency and increased capacity at the edge of the network can be achieved, to satisfy the requirements of the Internet of Things (IoT) ecosystem. If not properly orchestrated, the flexibility of the virtual network functions (VNFs) incorporation, in terms of deployment and lifecycle management, may cause serious issues in the NFV scheme. As the service level agreements (SLAs) of the 5G applications compete in an environment with traffic variations and VNF placement options with diverse computing or networking resources, an online placement approach is needed. In this article, we discuss the VNF lifecycle management challenges that arise from such heterogeneous architecture, in terms of VNF onboarding and scheduling. In particular, we enhance the intelligence of the NFV orchestrator (NFVO) by providing: 1) a latency-based embedding mechanism, where the VNFs are initially allocated to the appropriate tier and 2) an online scheduling algorithm, where the VNFs are instantiated, scaled, migrated, and destroyed based on the actual traffic. Finally, we design and implement an MEC-enabled 5G platform to evaluate our proposed mechanisms in real-life scenarios. The experimental results demonstrate that our proposed scheme maximizes the number of served users in the system by taking advantage of the online allocation of edge and core resources, without violating the application SLAs.

Grant numbers : SPOT5G (TEC2017-87456-P) and 5G Solutions ((856691)© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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