Research On Resource Management Strategy Based On SDCN

With the emergence of various new industries and the rapid development of the Internet industry,the scale of user networks has rapidly expanded,and various types of data traffic have exploded.This has brought huge challenges to the carrying capacity of traditional cellular communication networks and requires more effective resources.Management mechanism to allocate network resources.Because the traditional cellular network runs in a closed system,the application layer cannot perceive the operating status of the underlying network.Therefore,processing massive data requests on a limited link will result in unreasonable network resource allocation,resulting in low overall network effectiveness and inability to maximize the overall performance.Optimal angles to optimize resources,so the future network should have a more global perspective and powerful control capabilities.In this context,a new network architecture Software Defined Network(SDN)was created based on the Open Flow concept.Its core concept is to separate and decouple the control plane of the network from the data forwarding plane to achieve centralized control of the network and business-oriented Programming.Therefore,in combination with the future cellular network requirements and the core features of SDN,researchers will introduce SDN into traditional cellular networks to form a Software Defined Cellular Network(SDCN)architecture.This article will study resource management strategies under this network architecture.,So that network resources can be flexible and controllable.Introduce the network architecture of SDN,analyze the shortcomings in the operation of traditional cellular networks and the current research status of existing network resource management mechanisms,and introduce SDN with the idea of separation of control and forwarding into traditional cellular networks to form a new architecture SDCN.The background of the research architecture is here.Next,the scenario where air base stations and ground base stations coexist is selected,and UAV is used as an auxiliary resource for air access to realize the modeling and dimensionality reduction of research problems,and achieve the purpose of global optimal multi-dimensional resource configuration and deployment.In order to realize the centralized management and control of the control plane under the SDCN architecture,this paper designs and deploys four modules to cooperate in the controller,namely: global perception module,authentication access module,resource management strategy module and resource configuration module.First,use SDN's global awareness feature to collect information about the state of the entire network,establish a utility function about the overall network,and transfer the collected data to other functional modules for use;then use the authentication access module to achieve permission access control,and then you can trigger authentication.Use all available ground and air resources in the network;secondly,run the resource management strategy module to implement improved 3D UAV deployment and user association algorithms.In order to reduce the complexity of the algorithm,the problem model is reduced into two parts,and the results of the calculation are processed.The optimization from the local stage to the global stage calculates the global optimal model effect;finally,the controller sends the calculation result obtained by the resource management strategy module in the form of a "service flow table" to the relevant network entity Perform real-time matching updates.Through the experimental platform to simulate the real network traffic scenario for simulation analysis,the experimental results of the resource management strategy based on SDCN in this paper are obtained,and then two sets of performance comparison experiments are completed with different deployment scenarios and the utility function and throughput of different network architectures.The experimental results show that the resource management strategy in this paper can achieve more flexible and effective resource allocation,and achieve the global optimum in the research scenario.