Resource optimization scheduling and allocation for hierarchical distributed cloud service system in smart city

Abstract

With the support of 5G system, the hierarchical distributed cloud service network model (HDCSN) is proposed. The model consists of three levels: Access Cloud + Distributed Micro Cloud + Core Cloud, which meets the basic requirements of IMT-2020 (5G) and 3GPP for network system architecture. On the basis of access cloud, the distributed micro-cloud system of Smart City is deployed to migrate the service capabilities of the remote core cloud server to the local area. Users can obtain high-quality low-latency application services from the micro-cloud server in the local area. A resource description model based on resource graph and hierarchical resource vector is established, which enriches the Smart City service mode of IaaS cloud platform and provides a structural basis for optimal scheduling of cluster resources. A multi-node system resource graph scheduling and allocation algorithm VCE-PSO based on particle swarm optimization is proposed to optimize the response speed and resource efficiency of multi-node collaborative scheduling. The example shows that the above key technologies significantly improve 5G. The scheduling optimization and utilization efficiency of various resources in the hierarchical distributed cloud service for the Smart City effectively reduces the response time of the tenant resource request and optimizes the performance of system resource scheduling on the cloud platform.