关键词: QoS历史数据, 云服务, 服务选择, 时间序列预测

Abstract: For further analysis of the frequent variation in the QoS performance, the existing cloud service selection based on QoS historical data is improved. Firstly, in the original algorithm, the criteria weights of service decision-making in each period are calculated by entropy method based on the average QoS historical data. To further capture the frequent variation in QoS performance, the process to obtain the criteria weights is improved, this paper prefers to calculate the weights by entropy method based on the period’s QoS data rather than based on the overall average QoS historical data. Secondly, it uses time series forecasting ARIMA model to forecast the future QoS data, these data can be added into the original data set to generate a new data set, and then service decision-making is done based on the new data set. Finally, in order to evaluate two improvements, three experimental models are proposed for experiment progressively, then it analyzes the performance of the improved algorithm based on the comparison of experimental results.

Key words: QoS historical data, cloud service, service selection, time series forecasting