关键词: 云计算, 预测, GM（1, 1）模型, 多项式回归模型, 马尔科夫链, 布谷鸟搜索算法

Abstract: Discuss the characteristics of cloud computing resources load and the role of short-term load prediction. Polynomial regression model is used to optimize the GM（1，1） prediction results. Markov chain is empolyed for secondary optimization. The Cuckoo search algorithm is adopted to re-optimize the gray prediction model again. On this basis, the multi-step optimized GM（1，1） model is estbilished. Experimental results show that, compared with other forecasting models, for short-term resource load forecasting in cloud computing environment, the proposed model has higher prediction accuracy and achieved good predictive performance. The proposed method can provide decision support for efficient resource scheduling and management in cloud computing.

Key words: cloud computing, prediction, GM（1, 1） model, polynomial regression, Markov chain, Cuckoo search