基于IFTS的云计算网络动态负载均衡方法

针对云计算网络节点的异构性、资源配置的差异性和用户需求的不确定性等因素导致云计算网络极易出现负载不均衡的问题,在分析云计算节点负载模糊时序变化特性的基础上,构建了基于直觉模糊时间序列(IFTS)预测的云计算网络动态负载均衡模型,提出了基于IFCM的云节点计算资源自平衡方法,设计了基于IFTS预测的主动控制和基于反馈的被动调控相结合的虚拟机调度机制,并给出了云计算网络动态负载均衡策略,增强了云资源池的智能化管理水平,提升了云计算系统的整体性能.最后,通过典型实例验证了该方法的有效性和优越性.

The dynamic load balancing method of cloud computing network based on intuitionistic fuzzy time series

Aiming at the problem that the cloud computing network is prone to load imbalance, for the cloud computing network node heterogeneity, the differences of the allocation of resources and users demand uncertainty factors, on the basis of analyzing the fuzzy temporal variation characteristics of cloud node load, the dynamic load balancing (DLB) model of cloud computing network based on intuitionistic fuzzy time series (IFTS) is proposed. Meanwhile, the self-balancing algorithm for cloud node computing resource based on IFCM is proposed, the virtual machine scheduling mechanism based on mixing together the active control based on IFTS prediction and the virtual control based on feedback is designed, and the cloud computing network dynamic load balancing strategy is presented, which effectively enhances the intelligent management level of cloud resource pool, improves the overall performance of cloud computing system. Finally, the validity and superiority of the proposed method are verified by a typical example.