In cloud computing, virtual machine (VM) placement plays a crucial role in data center (DC) management, as different ways of VM placement may require different system resources. As Cisco research reveals that virtualization of DC increases traffic within the DC and causes network bandwidth to become scarce resource, recent researches have been focusing on traffic-aware VM placement. However, previous traffic-aware VM placement schemes treat the VM placement as a static process in that they do not take into account the impact of the current placement decision on the subsequent placement. In this paper, we thus propose a novel online traffic-aware VM placement scheme. Our scheme views VM placement as a context-sensitive dynamic process in that the decision of every step of the placement is made aiming at helping the subsequent steps of placement to reduce the required network bandwidth in the long run. In our scheme, we consider not only inter-VM traffic but also the bandwidth constraint of a physical machine (PM) when making a VM placement decision. To realize our objective, we put those VMs with close end time in the same or close proximity PMs so that when the VMs are terminated, one can make enough room for the future arrivals so as to not only minimize the number of active PMs but also reduce networking costs. We conduct extensive simulations to verify the superiority of our scheme in terms of networking costs and energy consumption. Simulation results show that our scheme outperforms improved-best-fit-decreasing (IBFD) scheme, a revised best-fit version that takes inter-VM traffic into account, by 30%–40% on network cost under various scenarios. Our scheme also promises 10%–25% power savings compared with IBFD.

在云计算中，虚拟机（VM）的放置在数据中心（DC）管理中起着至关重要的作用，因为不同的VM放置方式可能需要不同的系统资源。思科研究发现DC的虚拟化会增加DC内的流量并导致网络带宽成为稀缺资源，因此最近的研究一直集中在流量感知的VM放置上。但是，先前的可感知流量的VM放置方案将VM放置视为静态过程，因为它们没有考虑当前放置决策对后续放置的影响。因此，在本文中，我们提出了一种新颖的在线流量感知VM放置方案。我们的方案将VM放置视为上下文敏感的动态过程，因为对放置的每个步骤进行决策都是为了帮助从长远来看减少后续的放置步骤，以减少所需的网络带宽。在我们的方案中，在做出VM放置决策时，我们不仅考虑VM之间的流量，还考虑物理机（PM）的带宽约束。为了实现我们的目标，我们将那些具有接近结束时间的VM放置在相同或接近的PM中，以便在VM终止时，可以为将来的到来留出足够的空间，从而不仅可以将活动PM的数量降到最低，还可以降低网络成本。我们进行了广泛的仿真，以验证我们的方案在网络成本和能耗方面的优越性。仿真结果表明，在各种情况下，我们的方案的性能优于改进的最佳匹配降低（IBFD）方案（一种考虑了VM间流量的修订的最佳匹配版本），其网络成本降低了30％至40％。与IBFD相比，我们的方案还有望节省10％至25％的功耗。