Jixian Zhang1, Ning Xie1, Xuejie Zhang1, Kun Yue1, Weidong Li2,*, Deepesh Kumar3
CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 123-135, 2018, DOI: 10.3970/cmc.2018.03728
Abstract 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… More >
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