云计算环境下实体的多属性高效率评估策略设计

鉴于当前在云计算的实体信任评估领域所实施的方法策略无法满足云计算环境的动态模糊性,以遗传自适应学习算法为理论基础,在云计算环境下的信任管理过程中,针对动态评估高效率的需求,设计了多属性信任关系的动态评估模型。其可以评估分析信任管理过程实体的多属性问题,同时可以在持续的评估过程中,自主的学习,使其评估分析的执行能力逐渐提升,最终能够满足上文中阐明的高效性与动态性的要求。经过实验分析表明,本文所设计的模型在直接面对实时变化的云计算网络环境实体参数时,其可以自适应的调整评估策略规则,最终克服了云计算环境的动态模糊性,对实体的多个属性进行了综合评估。

Multi-Attribute High-Efficiency Assessment Strategies Design of Entity in Cloud Computing Environment

In view of the current methods and strategies implemented in the field of cloud computing entity trust evaluation can not meet the dynamic fuzziness,the paper based on the algorithm theory, for the dynamic assessment high efficiency needs in the trust management process adaptive learning of cloud computing environments, designs a dynamic evaluation model of multi-attribute trust relationships. It can evaluate the entity multi-attribute problems of the trust management process, while in the ongoing evaluation process, independent learning, so that implementation capacity assessment analyzes gradually improve and eventually be able to meet the efficiency and the dynamic nature requirements of set forth above. After experimental analysis, results show that while the model designed by this paper face to the real-time entity parameters changes in cloud computing network environment directly, it can adjust its assessment of policy rules adaptively , and ultimately overcome the dynamic cloud computing environments fuzziness of multiple properties entities conducted a comprehensive assessment.