基于网络感知的两阶段虚拟机分配算法

提出了一种基于网络感知的两阶段虚拟机分配算法(NWTP).首先,针对现代数据中心网络拓扑的随机性(树形、服务器和光纤混合),根据交互对象的不同,将虚拟机的带宽请求分为网内带宽和网间带宽两种.其次,将虚拟机的分配过程分解成带宽区域划分和物理主机分配两个彼此连续的阶段,建立网络感知模型.然后,利用流水线技术将带宽区域划分和物理主机分配看作两个连续的工序,并发进行分配处理.在带宽区域划分环节,利用节点介数和聚集系数动态感知物理主机的稳定性,通过差异化的分配策略为虚拟机子集选择合适的物理主机区域.在物理主机分配环节,将更多的虚拟机分配到负载方差最大的物理主机上,提高虚拟机网内带宽的节约度,均衡物理主机的资源负载.最后,对NWTP,遗传GA,模拟退火SA,贪婪GR四种算法进行大量的仿真实验,从分配时间、延迟、吞吐率、CPU利用率、带宽利用率和物理主机使用情况六个方面验证了NWTP算法的性能.

A Network-aware Two-phase Virtual Machine Allocation Algorithm

This paper proposed a two-phase network-aware virtual machine allocation algorithm (NWTP). Firstly, based on the randomness (the mixing of tree topology, servers and fiber) of modern data center network topology, the bandwidth requests of virtual machines were divided into two types of inner-bandwidth and outer-bandwidth according to the difference of interactive objects. Secondly, the virtual machine allocation requests were decomposed into two successive phases, and the corresponding network-aware model was established. Thirdly, pipelining technology was developed to regard the bandwidth region partitioning and physical host allocation as two consecutive steps, and to conduct parallel processing. For bandwidth region partitioning phase, the stability of physical host was dynamically perceived by using node betweenness and clustering coefficient, addressing differential allocation strategy to select the appropriate physical host set for the virtual machines subset. For the physical host allocation phase, more virtual machines were allocated to physical host resources with the largest load variance, which saved inner-bandwidth of data center and balanced physical hosts load. Finally, by comparing with the genetic algorithm GA, the annealing algorithm SA and greedy algorithm GR were simulated. Numerical results have shown the performance of NWTP in allocation time, network delay, network throughput rate, CPU utilization, bandwidth utilization and physical host usage.