Distributed Orchestration of Service Function Chains for Edge Intelligence in the Industrial Internet of Things

Network virtualization techniques are promising to overcome the obstacle of applying and expanding costly traditional networks in the industrial Internet of things (IIoT). Artificial intelligence (AI)-enhanced distributed resource management in edge networks has aroused researchers’ widespread attention. However, dynamically arrived service requests and limited edge resources complicate the service scheduling issue. In this article, we establish a dynamic network virtualization technique enabled service function chain (SFC) orchestration framework in IIoT, formulate the joint optimization problem to maximize total utility and decompose it into two subproblems, i.e., SFC selection and dynamic SFC orchestration. A dynamic orchestration of SFC (DOS) scheme, consisting of resource-aware matching algorithm and averaged multistep double deep q-network algorithm, is designed to embed SFC requests distributedly on the optimal virtualized network function chains. At last, we validate the superiority of our proposed DOS scheme by experimental results.

I. Introduction

The prosperity of the fifth-generation communication technology (5G) has promoted the revolution of the industrial Internet of things (IIoT). Billions of 5G-enabled devices enrich the provided network services while they complicate the application scenarios, including device information collection, ultrahigh definition video monitoring, product quality inspection, automatic guided vehicle, remote control, augmented reality-assisted diagnosis, and so on [1]. Traditional network framework relies on expensive dedicated hardware or devices, such as firewall, intrusion detection system, and gateway [2]. Costly operations encumber the expansion of the network capability in IIoT. Thus, an innovative network framework is needed to cope with these challenges.