基于软件定义网络的反饱和分组云负载均衡

Software defined network based anti-saturated grouping cloud load balance

云计算中统计复用是其显著特点,通过使用虚拟化技术可以提高物理资源利用率。针对云虚拟机集群需要考虑资源利用的负载均衡问题,面向OpenStack云平台,提出基于软件定义网络(SDN)的反饱和分组负载均衡(ASGS)方法。云主机按权值分配到不同的分组,SDN控制器利用探针根据不同分组周期性获取云主机负载。当请求到来时,均衡器以每组云主机平均权值为概率,随机选择一组,并在组内通过轮询选择一台合适的后端。为避免某台后端出现突发请求利用资源过多造成的云主机宕机现象,对较高权值的云主机预先加上一个参数,增高权值,使其处于高负载状态,让其接收更少的请求。实验结果表明,所提算法使各云主机不管请求量如何变化,随着时间的变化集群中云主机的资源利用率的标准方差比随机和轮询波动更小,更趋近于0,使得云主机集群的负载更均衡。

In the cloud computing,the statistical multiplexing is a remarkable character,and the utilization efficiency of physical resource can be improved through the virtual technology. Aiming at the load balancing problem of the resource utilization needed to be discussed in the cloud virtual machine cluster,a Software Defined Network（ SDN） based AntiSaturated Grouping Strategy（ ASGS） method was proposed according to the Open Stack cloud platform. The cloud hosts were separated into different groups based on their weights,and then the load information of cloud hosts were obtained by the SDN controller which used the probe with different groups periodically. When a request came,a group was selected randomly using the average weight of each group cloud hosts by the load balancer,and a proper backend was chosen by the polling method within the group. In order to avoid the cloud host downtime caused by the sudden increased requests for too many resources of a backend,the cloud host with higher weight was given a default parameter to increase the weight,and then the host would receive fewer requests on the higher load status. The experimental results show that,whatever the request number changes,the resource utilization standard variance of the proposed ASGS is always smaller than the random and round robin methods when time varies,which is nearly 0. The proposed ASGS has better load balance for the cloud host cluster.