改进QoS的云服务评价模型

摘要

针对云服务具有不确定性与大规模性,传统QoS的云服务评价模型工作机制灵活性不强,回报率低下等问题,设计改进QoS的云服务评价模型,对传统QoS的云服务评价模型的QoS属性项目进行细化,并利用熵值法为各项QoS属性项目进行比重取值.在改进模型的评价过程中,先针对实时数据进行重点评价,再结合以往数据特征对评价结果做出修正,并将修正结果输入未来预测时间,指导下次QoS云服务评价工作,以提高模型可靠性.同时将传统模型资源整体切入形式改为模块化切入形式,增添网络用户反馈机制与QoS监控机制,使评价服务更加完善.实验结果表明,改进QoS的云服务评价模型的服务内容选择性强,更能满足网络用户需求.%The cloud service has uncertainty and large-scale feature,and the traditional cloud service evaluation model for QoS has poor flexibility of working mechanism and low rate of return. Therefore,the improvement of cloud service evaluation model for QoS was designed.The QoS attribute items of the traditional cloud service evaluation model are refined,and their proportion values are calculated with the entropy method. In the evaluation process of the improved model,the real-time data is evaluated emphati-cally;the evaluated result is corrected in combination with the previous data features;the corrected result is input into the fu-ture prediction time to guide the QoS cloud service evaluation at the next time and improve the model reliability. The integrated pitching-in form of the traditional model resources is replaced by the modularized pitching-in form. The network user feedback mechanism and QoS monitoring mechanism are added to perfect the evaluation service. The experimental results show that the improved cloud service evaluation model for QoS has strong selection of service content,and can meet the needs of network users.