5G network-oriented hierarchical distributed cloud computing system resource optimization scheduling and allocation

As the core technology of the next generation mobile communication system, the development of 5G key technologies needs to be able to efficiently and effectively support massive data services. Aiming at the impact of massive data traffic on mobile communication networks in 5G communication systems, this paper proposes a 5G-oriented hierarchical distributed cloud service mobile communication system architecture. The model consists of a cloud access layer, a distributed micro-cloud system, and a core cloud data center. The distributed micro cloud system consists of multiple micro clouds that are deployed to the edge of the network. The service content in the core cloud data center can be deployed and cached to the local micro cloud server in advance to reduce repeated redundant transmission of user requested content in the network. Aiming at the problem of how to determine the migration object when dynamically optimizing the resource structure, a heuristic function-based dynamic optimization algorithm for cloud resources is proposed. The experimental results show that the dynamic expansion algorithm of cloud resources based on dynamic programming ideas can better improve the performance of virtual resources, and the dynamic optimization algorithm of cloud resources based on heuristic functions can effectively and quickly optimize the resource structure, thereby improving the operating efficiency of user virtual machine groups. An efficient resource allocation scheme based on cooperative Q (Quality) learning is proposed. The environmental knowledge obtained by the base station learning and exchanging information is used for distributed resource block allocation. This resource allocation scheme can obtain the optimal resource allocation strategy in a short learning time, and can terminate the learning process at any time according to the delay requirements of different services. Compared with traditional resource allocation schemes, it can effectively improve system throughput.