基于量化特征的云资源平台自适应调度方法

Adaptive Scheduling Method of Cloud Resources Platform Based on Quantitative Characteristics

通过对云资源平台的自适应调度设计,优化整合云存储空间资源,提高系统的运行效率和资源利用率。在云资源平台任务执行中收到用户行为特征干扰因素较多,调度响应出现时滞,传统方法采用基于时间尺度分析的云资源调度方法,当资源出现随机性干扰时受到网络延迟的影响较大,性能不好。提出一种基于量化特征提取的云资源平台自适应调度方法。构建资源调度平台的总体框架结构,进行资源信息特征提取,采用云资源量化特征提取结果作为调度系统的输入函数,对多源资源信息系统访问特征进行最小方差估计,整个调度过程是一个严平稳的随机过程,通过量化特征提取,能保证对云资源各个调度节点的遍历历经性,提高调度准确性。仿真结果表明,采用个算法能有效实现对云资源平台的自适应调度,抗干扰能力强,资源利用率较高。

Through the design of adaptive scheduling of cloud resources platform, cloud storage space optimization and inte-gration of resources, improve the utilization rate of the system operation efficiency and resources. To receive greater interfer-ence characteristics of user behavior factors in the cloud resource platform during task execution, scheduling in response to the occurrence of delay, the traditional method is using the cloud resource scheduling method based on time scale analysis, when resources appear random disturbance affected by network latency is larger, the performance is not good. This paper proposes an adaptive scheduling cloud resources platform quantization method based on feature extraction. The overall frame structure construction of resource scheduling platform of resource information, feature extraction, feature extraction using cloud resources quantitative results as the input function of scheduling system, the characteristics of multi-source in-formation resources access system for minimum variance estimation, the scheduling process is a Yan Ping steady stochastic process, through quantitative feature extraction, can guarantee to cloud resources of all scheduling the node traversal through sex, improve the scheduling accuracy. The simulation results show that, using the algorithm can effectively realize adaptive scheduling of cloud resources platform, strong anti-interference ability, high resource utilization rate.