Research On The Monitoring And Management System Of Virtualized Data Center

Virtualization technology effectively solves the problems such as waste of resources and management difficulties in traditional data center. It implements distribution of different functions and tasks by creating virtual machines to share physical equipment resources and using limited physical resources to run multiple operating systems. The technology of virtual machines’ migration between hosts already has extensive and further research which can achieve the goal of load balancing and hot release. But in application, many businesses’virtualized data center adopts static management of recourses that allocates quota resources when creating virtual machines. It cannot adjust dynamically according to the load demands at runtime which would cause lack of resources. Besides, with the increasing scale of clusters, the efficiency of artificial management will greatly reduce. Accordingly, it can improve service quality of the active data center and economize human resources to build a real-time monitoring system of cluster, automatically monitor the running state of all nodes and virtual machines, and make a reasonable resource allocating management based on real demand.In this paper, we studied the key technologies in designing and implementation of the monitoring and management system of virtualized cluster. Combined with previous researches, the works of this paper are follows:1. Based on current technologies of dynamic resource allocation in virtual machine and live migration, this thesis designed a framework model of cluster monitoring and management system which divides the cluster into center node and work node that are separately responsible for all nodes’monitoring of cluster and virtual machine monitoring inside the node. The nodes can also adjust automatically when the hotspot appears because of increasing demand.2. Work node monitors the running state of each virtual machine on it in real time. When virtual machine’s application load increase and the initial allocated resources are not enough to meet the demand, the resource utilization rate will reach the threshold followed a warning message. We build a model to forecast load relying on historical records and dynamically allocate resources using the algorithm to guarantee the virtual machine has enough recourses to run application in case of decline of quality of service.3. Center node is in charge of monitoring all nodes in cluster in order to make migration scheme for hot node which cannot ensure its virtual machines’quality of service because of node’s load increase and remaining resources decrease. The model is built based on forecast migration cost with memory size and page modifying speed to select virtual machine to migrate. The load sensitive target node selection algorithm is designed to determine a target host with the state of load and resources to place virtual machine. Reasonable simulation experiments are performed to verify the good effects of virtual machine selection algorithm.