Hybrid Services Collaborative Resource Scheduling Strategy towards Artificial Intelligence of Things

Abstract

The increasing number of Artificial Intelligence of Things (AIoT) devices at the edge layer brings serious challenges to the traditional access network architecture, which results in a decrease in data transmission due to different QoS requirements. To improve the QoS of the URLLC service and mMTC service in the AIoT, a Hybrid Services Collaborative Resource Scheduling Strategy (HSCRS) is proposed. First, a multi-layer collaborative resource scheduling framework for the AIoT hybrid services is designed based on the F-RAN. Then, a throughput weighting model for hybrid services is constructed to analyze the throughput characteristics of mMTC service and URLLC service. Furthermore, a sub-channel allocation and power control method is designed to solve the resource scheduling strategy of hybrid services. Experimental results show that the proposed method can largely improve the network throughput performance.