Optimize The Design And Realization Of Enterprise Cloud Computing Resource Management Programs

Recently, cloud computing is a area of grid computing in scientific research and commercial areas of new research and development trends. How to solve the enterprise cloud computing environment resource management and scheduling is a complex and extremely challenging and important issues. In this paper, the company's cloud computing Platform resource management product Excalibur as the research object, in order to cloud computing and cloud computing enterprise resource allocation, scheduling, requests for programs, based on the resources of the enterprise cloud computing services were studied, of which obtained the limitations of existing proposed optimization method to solve these defects.This paper studied the cloud computing and enterprise cloud computing resource management related theory and technology, analysis of the Excalibur program of the original contract for the supply and demand of resources and resource requirement of the configuration in the program, the original program does not meet the user to apply the resources and system scheduling resources. Therefore,the problem of the contract for the supply and resource requirement have been reseached new program in this paper and(1) Designed a new resource contract-Pay-Per-User Contract in the thesis, the new contract's definition of resource allocation, contract life cycle, and contract resource allocation methods, allows users to submit the contract can not stick to the original contract_Reservation contract limits the number of resources, improved use of resources and scheduling flexibility.(2)For the defect which can not meet user demand, the paper design and implement user-customized resource scheduling program and based on another problem for resources type, making scheduling of resources increasing users' requirements for request resources in simpler way.(3) The paper added a new resource type---resource type of computation in other to prevent singleness. At last, this article for improving the system are tested for functional and performance. Test results show that:function, improved resource scheduling more perfect, the allocation of resources has become more balanced, and in accordance with the desired target management and scheduling cloud computing resources. For the performance is concerned, the optimized program is also more humane, better meet the product design requirements, the overall sound performance than the original program. This study achieved its expected goals, to meet the cloud computing system resource scheduling needs.