Intelligent Latency-Aware Virtual Network Embedding for Industrial Wireless Networks

Abstract

The growing popularity of industrial wireless networks (IWNs) is driven by various applications with stringent timeliness requests. However, the ossification, deep-rooted in the one-application one-network architecture of traditional IWNs, impedes the evolution of IWNs toward smart factory. As a solution, the slice-based network virtualization (NV) breaks the tight coupling between applications and network infrastructure, and thus provides a more flexible and scalable IWN architecture. The application of NV relies on the algorithms that instantiate multiple virtual networks (VNs) on a substrate infrastructure, known as VN embedding (VNE). However, existing VNE algorithms are not necessarily optimal for IWNs due to the absence of QoS-compliant capacity. To this end, so called iVNE, an intelligent latency-aware VNE scheme, is proposed to provide deadline guarantee for various industrial VNs (IVNs), which involves both static embedding and dynamic forwarding. In the static stage, an anypath embedding algorithm is introduced for the new arrival of IVNs so that their resource demands and deadlines can be satisfied with coarse grain. Then, a dynamic anypath forwarding method is incorporated into iVNE to offer intelligent latency sensing via deep ${Q}$ -learning, and thus forwarding adjustments can be made timely to address the dynamic changes of link quality and network workload. The simulation results are provided to demonstrate the learning efficiency as well as the ability of load-balancing through responsive forwarding under dynamic environment.