The upcoming fifth generation (5G) of mobile communications urge software defined networks (SDN) 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 paper, 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 i) a latency-based embedding mechanism, where the VNFs are initially allocated to the appropriate tier, and ii) an online scheduling algorithm, where the VNFs are instantiated, scaled, migrated and destroyed based on the actual traffic. Finally, we design and implement a 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.
The upcoming fifth generation (5G) of mobile communications brings new paradigms, such as network slicing and automation, to the forefront. Cloud computing and network function virtualization (NFV) constitute two fundamental key enablers towards the implementation of these new paradigms. On the one hand, computational functionalities are no longer limited to distant servers, but they are coming closer to the end user through Multi-access Edge Computing (MEC) technology, thus creating a multi-tier cloud architecture in modern networks. On the other hand, going beyond the existing rigid architectures, NFV enables the flexible and on-the-fly creation and placement both of application and network functions, aiming at satisfying the diverse application requirements and optimizing the management of the heterogeneous (network, computational and storage) resources. In this paper, we discuss the challenges that arise in a MEC-enabled 5G architecture that supports the flexible placement/migration of network and application virtual network functions (VNFs), orchestrated by an NFV Orchestrator (NFVO) with admission management functionalities, able to manage on-the-fly the network functions and resources. Finally, we describe in detail a MECenabled testbed architecture that facilitates the development and testing of such solution in the context of 5G networks.
The Internet of Things (IoT) ecosystem, as fostered by fifth generation (5G) applications, demands a highly available network infrastructure. In particular, the internet of vehicles use cases, as a subset of the overall IoT environment, require a combination of high availability and low latency in big volumes support. This can be enabled by a network function virtualization architecture that is able to provide resources wherever and whenever needed, from the core to the edge up to the end user proximity, in accordance with the fog computing paradigm. In this article, we propose a fog-enabled cellular vehicle-to-everything architecture that provides resources at the core, the edge and the vehicle layers. The proposed architecture enables the connection of virtual machines, containers and unikernels that form an application-as-a-service function chain that can be deployed across the three layers. Furthermore, we provide lifecycle management mechanisms that can efficiently manage and orchestrate the underlying physical resources by leveraging live migration and scaling functionalities. Additionally, we design and implement a 5G platform to evaluate the basic functionalities of our proposed mechanisms in real-life scenarios. Finally, the experimental results demonstrate that our proposed scheme maximizes the accepted requests, without violating the applications' service level agreement.
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