基于多约束值的动态资源调度策略

Dynamic Resource Matching Based on Multi Constraint Value

负载均衡问题本质是资源调度问题,需考虑到资源合理分配、闲置服务集群有效利用、实现负载分摊,最终降低运行节点负载量。本文系统地研究了虚拟网络资源调度模型和相关技术,结合云计算和虚拟化网络特点,构建了虚拟网络调度模型,并实现了一种基于多约束值的动态资源匹配(Dynamic resource matching based on multi constraint value,DRMV)策略。当任务请求到达,DRMV算法根据任务大小、节点负载量、功率及网络带宽等多个约束值对任务和服务节点进行排序处理。同时,为了降低任务和服务节点匹配时间与成本消耗,DRMV算法利用服务节点实际负载反馈情况,动态调节系统负载。

The essence of load balancing is resource scheduling problem. In order to achieve load sharing,the rational allocation of resources should be given to considerate and the idle service clusters should be given to effective utilize. Ultimately,reduce the load of the running node. Systematically studied the virtual network resource scheduling model and some related technologies,build a virtual network scheduling model under cloud environment according to the characteristics of cloud computing and virtualization of network,and proposed DRMV（Dynamic resource matching based on multi constraint value,DRMV）strategy. When a request arrived,the DRMV sorted and processed the task and service node based on the size of task,the node load,power and network bandwidth and other constraint values. At the same time,in order to cut down the time and cost consumption of matching task and service nodes,DRMV used the service node＇s feedback of actual load,dynamically adjusted the system load.