Research On Active Service And Optimal Configuration Management For Product Design Resource

With the increasingly fierce competition among enterprises,it is necessary for enterprises to realize rapid,effective and personalized product supply.In the process of product design,in order to shorten the development cycle of products and improve the efficiency of resource service,the active service of design resources is realized,the active acquisition problem of design resource service requirements is solved,and try to find out the resources which are suitable for the designer's real needs from the massive network design resources,push the appropriate design resources to the designer quickly and efficiently.In order to avoid the huge challenge of the large scale and complex data source to the maintenance personnel of the network design resource management system,this paper puts forward the method of the optimal configuration and automatic management of the network design resources.To solve the above problems,this paper makes the following research:(1)Concept and theoretical basis of design resource service.The basic theory is defined and classified,which provides the precondition for the research on how to achieve design resource services efficiently.In order to get a deep understanding of the characteristics of the flow of resources and the transfer process in the related fields,this paper defines and analyzes the three areas of design resources,design resource service requirements and cloud design resources.(2)Active acquisition method of design resource service requirements based on context awareness.In order to be able to obtain design resources service requirements actively,based on the analysis of the characteristics of the context aware reasoning layer,construct the context aware service system which can access the requirement of design resource service actively.Bayesian approach is used to make the design resource type,and according to the characteristics of different situations,in order to select the appropriate method which can be integrated into the recommend,a collaborative filtering algorithm based on the preference of fusion resources is proposed,by calculating the expected value of the service requirements of a number of design resources and comparing the its size,to realize the active acquisition of design resources service requirements based on the context aware.(3)Active feedback method of cloud design resource nodes for designers' demand and preference.Cloud design resource modeling for product design is carried out,on the basis of the cloud design resource response capability model and the designer's demand and preference model,construct the cloud design resource scheduling mechanism based on negative feedback,by solving the scheduling mechanism,the similarity matching between the cloud design resource response capability and the demands of designers is realized,and feedback the cloud design resource node which has higher matching degree to designers,thus the utilization ratio of resources is improved.(4)Adaptive optimal configuration management method of cloud design resources.Construct an adaptive allocation model of cloud design resources based on neural network and multi objective genetic algorithm,the neural network prediction algorithm is used to predict the resource load,and propose the virtual machine migration request according to the predicted value.In order to provide the best migration strategy for virtual machines,the multi-objective optimization genetic algorithm based on hybrid grouping encoding is introduced into the virtual machine resource management,at the same time,reduce the virtual machine migration times and physical nodes' number,finally,the adaptive configuration management of cloud design resources is realized.Simulation results and analysis show that the method can be used to ensure the low rate of agreement between energy consumption and service level,improve the service efficiency and quality of design resources.