基于多目标遗传算法的云服务系统资源调度失效局部最优感知方法

Multi-objective Genetic Algorithm Based Local Optimal Sensing Method for Resource Scheduling Failure in Cloud Service System

针对当前资源调度失效感知效果不佳,可靠性和感知灵敏度的问题,提出基于多目标遗传算法的云服务系统资源调度失效局部最优感知方法,结合多目标遗传算法,通过资源调度的失效特征规律识别,对资源调度的失效特征规律识别方法优化,抽取受信任的云计算资源,识别和筛查资源失效特征归类,并对局部调度失效资源进行定位,构建云服务系统资源调度失效局部最优感模型,求解云资源局部调度失效区域定位规则。实验结果表明,该方法具有较高的可靠性和感知灵敏度,保证云服务系统资源调度失效感知结果的有效性。

Aiming at the current problems of poor perception effect,reliability and sensitivity of resource scheduling failurc,a local optimal perception method of resource scheduling failure in cloud service system based on multi-objective genetic algorithm is proposed.Combined with multi-objective genetic algorithm,through the identification of failure characteristics of resource scheduling,the identification method of failure characteristics of resource scheduling is optimized,trusted cloud computing resources are extracted,and the classification of resource failure characteristics is identified and screened,And locate the local scheduling failure resources,build a local optimal model of resource scheduling failure in cloud service system,and solve the location rules of the local scheduling failure area of cloud resources.Experimental results show that this method has high reliability and sensitivity to ensure the effectiveness of the perceived results of resource scheduling failure in cloud service system.