考虑价格因素的 并行模糊多准则时 变权重云服务决策

网络中云服务存储量的几何式快速增长使得云服务决策越加困难，为满足用户特殊需要并提供充足的决策依据，提出并行TOPSIS时变权重模糊云服务多准则决策算法.在并行TOPSIS改进中采用熵权重赋值形式赋予云服务相应的准则权重，使得权重的选择变得简单易行，并由此发展出时变权重提出改进TOPSIS评估机制，使用时变权重能够更好的对不同时间段的云服务质量（QoS）信息进行重要性区分，使得决策机制更加合理可信.然后基于分时模糊TOPSIS多准则决策机制，设计云服务选择的并行化融合决策框架，使得算法更趋近于工程应用.仿真结果显示，所提云服务决策算法可更有效的对QoS信息影响进行抑制，从而有效提高云服务调用的成功率.

Consider price factors parallel fuzzy multi criteria time-varying weights for cloud service decision

The rapid growth of cloud service storage of geometric network made the cloud service decision more difficulty, in order to meet the special needs of users and provide sufficient basis for decision making, here presented the parallel fuzzy multi criteria time varying weights algorithm for cloud service decision, which considered the price factors. In improved parallel TOPSIS algorithm, it used the entropy weight assignment to select the criteria weights of cloud services, which maked the choice of the weights to be simple and easy, and it presented time varying weights to improve the TOPSIS evaluation mechanism, it used time varying weights to distinguish the importance of different time periods for cloud services, which made the the decision mechanism more reasonable and reliable. Then, based on the multi criteria decision making mechanism of fuzzy TOPSIS, here designed the parallel decision fusion framework for cloud services selection, which makes the algorithm more close to engineering application. The simulation results showed that, the proposed algorithm could be more effective for inhibition the influence of QoS information for cloud services decision, which could effectively improve the call success rate of cloud service.