Management Of Resources In Cloud Based On OpenStack

In today's social cloud computing has become the well-known focus, it has been increasingly deep into our life around. With the development of cloud technology to expand the scale of cloud, cloud resources, the number of types is also increasing dramatically, so for the management of cloud resources have become increasingly heavy task. In the cloud resource management process, the waste of resources and resource loss is a primary consideration, a good resource management system must give attention to these two aspects, to ensure normal operation of the equipment at the same time reduce the depletion of resources to raise the utilization rate of resources.Based on such a technical environment, how to better manage cloud resources to reduce resource consumption and improve resource utilization to achieve load balance, is the most eager to solve the problem. Openstack is an open-source cloud computing platform project management. It supports almost all types of cloud environment, the project goal is provides simple implementation, can be expanded on a large scale, rich, uniform standards for cloud computing platform management, in order to provide software for the construction and management of public and private cloud. OpenStack as the most popular cloud platform management technology, and as an open source software is the focus of professional researchers to study the object. The OpenStack platform of cloud resource management technology based on the result of.In this paper, we study the dynamic expansion of the virtual machine resources, including the dynamic increase or decrease of the virtual machine resources. First of all, through the resource monitoring program to collect the amount of resources, according to the resources in the form of changes in the future of the amount of resources are expected to develop resource expansion program. Details are described as follows, first set the load threshold to determine the virtual machine resource utilization rate of the normal range; and for monitoring program set level, determine the resources in a load range, load range is divided into mild load and moderate load heavily loaded with three different levels, in the heavy load within the range of the frequency of monitoring dynamic changes, the purpose of doing so is can guarantee to obtain the most accurate and prompt data and monitoring program resource consumption to a minimum. Next to monitor the data to predict, to develop a suitable extension or contraction of the program. The research also includes the migration of virtual machines, including the selection of the source virtual machine and the distribution of the virtual machine and the destination server. Source virtual machine is realized by way of finding and server load similar virtual machine. In the study on the virtual machine and the target server allocation combined with a variety of optimization algorithm for multi objective ant colony optimization algorithm was proposed to, multi-objective ant colony optimization algorithm and virtual machine migration technology combination, to ensure that the virtual machine migration efficiency and stability, while reducing the depletion of resources and improve the resource utilization rate to ensure the load balance.