Aiming at the problem of resource scheduling optimization in enterprise management cloud mode, a customizable fuzzy clustering cloud resource scheduling algorithm based on trust sensitivity is proposed. Firstly, on the one hand, a fuzzy clustering method is used to divide cloud resource scheduling into two aspects: cloud user resource scheduling and cloud task resource scheduling. On the other hand, a trust-sensitive mechanism is introduced into cloud task scheduling to prevent malicious node attacks or dishonest recommendation from node providers. At the same time, in the cloud task scheduling, cloud resources are divided according to the comprehensive performance of resources, and the trust sensitivity coefficient of each type of task resources is calculated. Then, according to the trust sensitivity coefficient, the matching cloud tasks are selected for users. Through the comparison of simulation experiments, the customized fuzzy clustering cloud resource scheduling algorithm proposed in this paper reduces the user’s cost of selecting cloud service provider in the cloud resource scheduling. It not only embodies the principle of cloud resource allocation on demand but also can give full play to the advantages of cloud resources and improve the throughput of the whole cloud system and the satisfaction of cloud users.

中文翻译：

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企业管理云模式下资源调度的定性仿真算法

针对企业管理云模式下的资源调度优化问题，提出了一种基于信任敏感性的可定制的模糊聚类云资源调度算法。首先，一方面，采用模糊聚类的方法将云资源调度分为云用户资源调度和云任务资源调度两个方面。另一方面，信任敏感机制被引入云任务调度中，以防止恶意节点攻击或来自节点提供者的不诚实推荐。同时，在云任务调度中，根据资源的综合性能对云资源进行划分，计算出每种任务资源的信任敏感性系数。然后，根据信任敏感性系数，为用户选择匹配的云任务。通过仿真实验的比较，本文提出的定制模糊聚类云资源调度算法降低了用户在云资源调度中选择云服务提供商的成本。它不仅体现了按需分配云资源的原则，而且可以充分发挥云资源的优势，提高整个云系统的吞吐量和云用户的满意度。