Hybrid Services Collaborative Resource Scheduling Strategy towards Artificial Intelligence of Things
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: IoT and Edge/Fog Computing · Age of Information Optimization · IoT Networks and Protocols
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Grid Chongqing Electric Power Research Institute, Chongqing 401123, China
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Funding
State Grid Chongqing Electric Power Company · National Natural Science Foundation of China
References (23)
Show source-provided references
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