Resource Allocation And Optimization Of Network Range Based On Cloud Computing

In recent years,with the development of network and information technology,cyber security issues are increasingly prominent,network attack and defense has become the main form of network confrontation in various countries.The cloud-based network range is an important infrastructure for attack and defense drills.However,due to the diversity of target virtual machine resource requirements and the heterogeneity of physical machine resources,the resources of the network range are often not fully utilized,and easy to generate load imbalance problems.In this regard,this thesis mainly carried out the following research work:Firstly,the research status of network range and cloud computing resource scheduling is studied,and the research significance of this thesis is clarified.The definition of the network range resources,the current problems and the main solutions to these problems are described.In view of the difficulty of cloud computing experiments requiring a large number of clusters,it is determined to use the CloudSim cloud computing simulation platform for auxiliary experiments.Secondly,according to the imbalance of resource load caused by the heterogeneity of the network range resources,combined with the characteristics of the communication between the virtual machines in the network range only in the same scene,a multi-objective optimization for the network range is proposed with reference to the idea of ant colony algorithm.Virtual machine deployment algorithm.On CloudSim,the virtual machine deployment algorithm based on random algorithm and the virtual machine deployment algorithm based on optimal adaptation algorithm are compared experimentally,and the superiority of the algorithm is proved.Thirdly,the remapping problem between the virtual machine and the physical machine in the network range is studied.Combined with the characteristics of the maximum remaining life of the virtual machine in the network range,a virtual migration strategy for the virtual machine is proposed.The strategy uses the low threshold,the high threshold and the adaptive threshold to judge the overall load status of the network range,complete the load grouping of each physical machine in the network range;use the load prediction mechanism as the trigger mechanism of the migration strategy to eliminate the impact of the instantaneous load peak and avoid After the migration is triggered,the migration source virtual machine is selected according to the resource characteristics of the virtual machine,the maximum remaining life of the virtual machine,and the impact of the migration on the communication overhead;the physical machine whose load is lower than the low threshold is assigned to the migration target physical machine set.And use the best adaptive descent algorithm to determine the final migration target physical machine;propose a supplementary adjustment strategy,when the overall load of the system is lower than the low threshold,close some low-load physical machines to improve system resource utilization and reduce energy Consumption.Finally,the requirements of the network range system are analyzed,and the overall architecture of the network range,the architecture of the network range virtual environment module and related data tables are designed according to the requirements.Then the virtual environment of the network range system is developed by using the Django web framework and the OpenStack private cloud platform.The creation,use,and deletion of complex network virtual environments were tested.