An Optimized Virtual Machine Deployment Mechanism In Cloud Platform

Cloud computing is a new calculation model, which is presented in recent years. It is different from traditional deployment method that it can obtain the infrastructure services at the lowest cost. Cloud computing launches a groundbreaking innovation with its unique IT service hiring mode in the field of IT.Elastic Computing Cloud integrates of a large number of virtual resources through virtualization. It is not only easier to manage hardware resources, and can significantly improve the efficiency of the use of computing resources. It is beneficial for people to put more attention into business logic, reduce infrastructure investment, and the difficulty of maintaining infrastructure technology. Virtual resource deployment decides the. quality of services provided by cloud computing platform in the very great degree.In the usual method of deploying virtual machines, hosts are usually selected only based on hosts’current CPU conditions. It ignores the amount of resources occupied by the virtual machines, and does not adequately consider the load that the hosts can bear. The above can lead to the match between the hosts’performance and the load on virtual machines in poor. Inevitably it brings load imbalance caused b.y the irrational use of resources.In view of the above problems, this paper makes a deep research, the work of this thesis are summarized as follows:(1) This paper presents a model of selecting hosts automatically which can optimize deployment of virtual machines in cloud computing. The model can predict follow-up load conditions on hosts, including the server’s CPU, memory, hard disk, network bandwidth, in order to master servers’performance in future period of time.(2) In order to ensure loads relatively balance in the cloud platform, we also put forward the strategy of load balancing in the process of hosts’automatic selection:we set up a management layer in the model. The management server is responsible for handling users’virtual resource application, and implements the unified management on the host selection process so that the model chooses the most suitable server as the target host with overload hosts eliminated.(3) Host auto-selection algorithm based on the individual needs is the core algorithm of the model, which can pre-estimates resource consumption. The users can set different performance values and weights for the requested resource according to the application background. The model can quantify the request. Compared with the traditional method of deployment, the model optimizes the match between the resource requested and performance of hosts.The virtual machine deployment mechanism in this paper realizes the process of user self-selection, and hosts are automatically selected in the process of deployment. Quantitative requests in the model meet users’individual needs to a certain extent, so it is very suitable to apply to the cloud. Experiments show: the target host determined by the deployment mechanism can fully meet the user’s individual needs, and the system’s performance can also be effectively improved. It reduces the frequency of virtual machine migration, and the host clusters’load tends to be balanced, which is beneficial for the system to run stably.