云平台资源多层服务信息传输负载调度仿真

Load Scheduling Simulation of Cloud Platform Resource Multi-Layer Service Information Transmission

对云平台下资源多层服务信息的传输负载进行调度,能够有效提高云平台的服务质量。对信息传输负载的均衡调度,需要对云计算资源的整体特性进行抽样预测,对评估整个云平台资源多层服务所用时间,完成多层服务信息传输负载的均衡调度。传统方法对云计算集群中的参数向量变化进行实时衡量,得到参数向量的权重,但忽略了对资源服务话费时间的评估,导致调度精度偏低。提出一种信息传输负载均衡调度优化方法。利用DLB数学模型,对集群的负载均衡问题进行描述。对云计算资源的整体特性进行抽样预测,并对整个云平台资源多层服务所用的时间进行评估。通过休眠能耗估算模型和工作能耗估算模型建立云平台资源多层服务模型,根据云平台资源多层服务模型对资源进行合理调度,完成集群的负载均衡优化。仿真结果表明,所提方法的作业执行效率高,优化后的系统功耗低。

The traditional methods ignore the assessment of time consumption of resource service and lead to low scheduling accuracy.Therefore,this paper puts forward a method to optimize the load balancing scheduling for information transmission.Firstly,this method used DLB mathematical model to describe the load balancing problem of cluster.Then,our method sampled and predicted overall characteristic of cloud computing resource and evaluated the time spent by the multi-layer service of whole cloud platform resource.Through the estimation model of dormant energy consumption and the estimation model of working energy consumption,we built the multi-layer service model of cloud platform resource.Finally,we used the multi-layer service model of cloud platform resource to schedule resource properly.Thus,we could complete the load balance optimization of cluster.Simulation results prove that the proposed method has high efficiency in job execution and low power consumption in optimized system.