Resource allocation in auctions is a challenging problem for cloud computing.However,the resource allocation problem is NP-hard and cannot be solved in polynomial time.The existing studies mainly use approximate algor...Resource allocation in auctions is a challenging problem for cloud computing.However,the resource allocation problem is NP-hard and cannot be solved in polynomial time.The existing studies mainly use approximate algorithms such as PTAS or heuristic algorithms to determine a feasible solution;however,these algorithms have the disadvantages of low computational efficiency or low allocate accuracy.In this paper,we use the classification of machine learning to model and analyze the multi-dimensional cloud resource allocation problem and propose two resource allocation prediction algorithms based on linear and logistic regressions.By learning a small-scale training set,the prediction model can guarantee that the social welfare,allocation accuracy,and resource utilization in the feasible solution are very close to those of the optimal allocation solution.The experimental results show that the proposed scheme has good effect on resource allocation in cloud computing.展开更多
基金This research is supported by the National Natural Science Foundation of China(No.61472345,61762091 and 11663007)the Scientific Research Foundation of the Yunnan Provincial Department of Education(No.2017ZZX228)IRTSTYN,and Program for Excellent Young Talents,Yunnan University.
文摘Resource allocation in auctions is a challenging problem for cloud computing.However,the resource allocation problem is NP-hard and cannot be solved in polynomial time.The existing studies mainly use approximate algorithms such as PTAS or heuristic algorithms to determine a feasible solution;however,these algorithms have the disadvantages of low computational efficiency or low allocate accuracy.In this paper,we use the classification of machine learning to model and analyze the multi-dimensional cloud resource allocation problem and propose two resource allocation prediction algorithms based on linear and logistic regressions.By learning a small-scale training set,the prediction model can guarantee that the social welfare,allocation accuracy,and resource utilization in the feasible solution are very close to those of the optimal allocation solution.The experimental results show that the proposed scheme has good effect on resource allocation in cloud computing.
