Return
Virtual IoT Service Slice Functions for Multiaccess Edge Computing Platform
DOI:10.1109/JIOT.2021.3051652.png)
Abstract
En 中文
With the advancement of the Internet of Things (IoT), different use cases, such as smart factories, smart cities, and smart cars are being developed. Technologies, such as multiaccess edge computing (MEC) and network slicing are being researched to support various vertical use cases. However, simply utilizing network slicing and MEC is insufficient when providing a specific IoT service. Accordingly, there is a need for a method of arranging and operating common service functions (CSFs) used in the IoT platform at the edge of the network. In addition, it is necessary not only to deliver virtual CSFs but also to implement autoscaling policies of these virtual common service resources. This study extends the idea of resource slicing technologies for the IoT service layer. The IoT service layer exposes the virtual IoT CSFs as an IoT slice service to be provided in the form of virtual network functions (VNFs) with MEC applications on top of the network function virtualization infrastructure (NFVI) at the edge of the network. We propose a framework architecture for virtual IoT slice service orchestration, and illustrate how to instantiate the virtual IoT service functions in the existing centralized cloud to the MEC platform. We also propose an elastic computing algorithm of virtual IoT slice services functions(vIoT-SSFs) resources at the NFVI so that the IoT applications and underlying IoT resources can access vIoT-SSFs at the edge of the network.
Keywords:
Internet of Things
5G mobile communication
Network slicing
Edge computing
Quality of service
Computer architecture
Network function virtualization
Autoscaling policies
Internet of Things (IoT)
multiaccess edge computing (MEC)
network slicing
oneM2M standard
virtual network function (VNF)
virtualization of IoT service layer
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

