Network architecture and resource scheduling and allocation method based on network architecture

Abstract

The invention discloses a network architecture and a resource scheduling and allocation method based on the network architecture. The network architecture comprises an MEC layer, an MSCN layer and a vehicle layer, wherein the MEC layer comprises a plurality of road side units RSUs dispersedly arranged on a road. The method comprises steps of setting a jurisdiction area for each road side unit RSUon the road, and forming a cluster by all vehicles in the jurisdiction area, wherein the MSCN layer comprises a mobile auxiliary computing node of each cluster; selecting one vehicle from each subareaas a mobile auxiliary computing node, wherein at least one mobile auxiliary computing node is also used as a transmission controller at the same time, the vehicle layer includes all vehicles in eachcluster other than being used as mobility-assisted compute nodes. According to the network architecture, the advantages of a hierarchical network are utilized, fluctuation of communication performancecaused by different vehicle densities under an existing MEC architecture is solved, and the network architecture has good communication performance no matter whether the vehicle density is low or high.

Description

technical field [0001] The present invention relates to the technical field of resource scheduling and allocation, in particular to a network architecture and a resource scheduling and allocation method based on the network architecture. Background technique [0002] With the introduction of the concept of MEC (Multi-access Edge Computing, Multi-access Edge Computing), RSU (Roadside Unit, Roadside Unit) is considered as an effective service provider, which performs calculations related to resource allocation and data processing, Provide real-time applications for road vehicles. However, when an RSU communicates with a moving vehicle, the high mobility of the connection communication may affect the real-time performance of the service; moreover, the vehicle density will also affect the service performance. [0003] With the development of autonomous vehicles, researchers believe that real-time data from vehicles is an important and valuable data source for autonomous driving...

AI Technical Summary

Problems solved by technology

However, passive clustering is only suitable for applications in traffic network environments with low vehicle density, and is not suitable for applications in high-density environments.

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