摘要：There are now a vast array of heterogeneous cloud service resources, which makes it difficult to identify suitable services for the various types of cloud users. A classification of cloud service resources would help users find suitable cloud services more easily. We propose such a classification strategy, which has two parts. First, we improve the original naive Bayesian classification algorithm, designing a Bayesian classification algorithm based on feature similarity. Second, to improve the efficiency of the classification algorithm, we design a parallel programming model using the Hadoop platform. Simulation results show that the proposed classification strategy is feasible and effective, improving not only the resource classification accuracy but also greatly enhancing the processing efficiency for large-scale cloud service resources
关键词：Cloud Service;Resource Classification;Bayesian;Feature Similarity;MapReduce Programming Model
