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this paper puts forward the monitoring and measurement methods on energy consumption of virtual machine in the cloud data center, establishes energy consumption model of virtual machine system and virtual machine migration. The usual migration method of virtual machine uses heuristic algorithm to allocate virtual machine, its solution result is easily to be got into locally optimal solution, and this paper gives migration algorithm of virtual machine based on genetic algorithm on the basis of making research on genetic algorithm, it makes improvement on the target function in genetic algorithm, making application number of target node and migration time minimum on condition of meeting protocol of service class, so that it can realize energy conservation in data center. Introduction With the popularization and quick development [1, 2,3] of computer technology, the task request reaches in cloud computing platform becomes to be diversified. In order to meet task demand of different kinds, the calculation node in cloud data center constitutes hardware platform of cloud calculation has to keep open state for long time and wait for arrival of task, which will cause low application and high waste of cloud data center on energy consumption. Energy consumption model can be said to be one of the most important parts in cloud data center, when cloud data center is continually operating, we should make deep comprehension on users and administrators of cloud calculation, know their application way, so that make corresponding solution measures, so that it can reach target of optimization and energy conservation. At present, many servers of cloud data have the self-detection ability, they can measure some data components, but this single physical detection ability is obviously accords with future development idea of cloud data center, only quicker and effective energy conservation measures can make energy consumption modeling have cleanness . This paper tries to establish reasonable and reliable energy consumption model for cloud data center from layer of cloud infrastructure, and it compares with effect of different sampling ways and mathematical techniques on energy consumption model. On algorithm and test, it uses research outcome of energy consumption model put forward by this paper to demonstrate effectiveness of energy consumption model state by this paper, and this energy consumption model can be also applied to other research work on it. System structure on energy management of cloud computing It uses virtualized technology as core and fully considers resources application and load characteristics under cloud calculation environment, it makes effective monitoring management and optimization on energy consumption of cloud calculation, reduce total energy consumption of virtual cluster. It also provides calculation resources server on IT service, it can be indicated as DC = {H1,H2,...,HN}. It indicates calculation node, which is the physical server provides calculation ability, data center in distributed calculation, the node is divided into calculation node and storage node, data and file storage are in the storage node of NFS. The physical master is isostructural, it has the same calculation resources capacity(CPU, memory, disc), as the parasitifer, physical master International Conference on Applied Science and Engineering Innovation (ASEI 2015) © 2015. The authors Published by Atlantis Press 594 opertes isomeric virtual machine, it is provided by Vmware or XEN. Virtual machine is isomeric, bit it is not random isomerism, it has certain virtual machine category defined in advance VC(vm class) = {VCi,-,VCs], virtual machine of every category is isostructural, its resources occupancy is (resource)={R1,...,RS}. In order to record and describe state of current cluster, it adopts matrix to describe state in virtual cluster, the formula 1 is indicated as follows:

Modeling on Energy Consumption of Cloud Computing Based on Data Center