云计算中服务质量预测数据的信心建模

为处理服务质量(quality of service,Qo S)预测所用数据的不确定性,增加预测结果的信心值,使预测的Qo S值更可信,建立了量化Qo S预测中信心的概率模型。构建模型过程中,考虑了预测所用的Qo S数据项数量、数据的波动情况(数据偏差)以及数据随时间的衰减情况。数据项数量表明参与预测的数据多少对预测结果可信度的影响程度;数据偏差表明服务的实际Qo S值和预期值的一致程度;数据衰减程度表明随时间变化,数据对预测结果的影响程度。仿真试验表明,该信心模型能够准确有效地帮助用户选择满足其需求的服务。

Confidence model of QoS prediction data in cloud computing

In order to handle the uncertainty of data used in quality of service (QoS) prediction, increase the confidence value of prediction results, and make the QoS prediction more reliable, a probability model for quantifying the confidence in QoS prediction was built. In the process of building the model, the number of QoS data items used in prediction, the data fluctuation (data deviation), and the data decay over time were considered. The results show that the number of data reflects the impact of the number of QoS data used in prediction on the reliability of the prediction result, the data deviation reflects the consistency degree of the actual value and predicted value of QoS in service, and the data decay reflects the impact of data on the prediction result over time. The simulated test indicates that the confidence model can help consumers effectively select services based on their requirements.