Nowadays, with the development of wireless communication, people are relying on mobile devices heavily due to various application deployment and plentiful service experience of customers in wireless metropolitan area network (WMAN). The computing resources of the mobile devices are limited as they are restricted with physical size, battery capacity, etc. In order to release the resource limitation, cloudlet, an effective paradigm, is introduced to host the computing tasks offloaded from the mobile devices. Compared with the cloud computing, the cloudlets are deployed closer to provide customers with fewer task offloading delay. Currently, the offloaded task scale is increasing, which generates large quantities of energy exposure for task implementation among cloudlets. Taking advantage of live virtual machine (VM) migration technology, the energy consumption of cloudlets could be definitely reduced. But such migration across cloudlets also decreases the implementation performance of the tasks. Therefore, it is still a challenge to jointly optimize the execution performance and the energy consumption for cloudlet management in WMAN. In this paper, a novel virtual machine (VM) scheduling method is proposed to balance the implantation time and the energy consumption to cope with the above challenge. Specifically, a collection of available migration polices are obtained through heuristically searching of destination cloudlets for the running computing tasks. Then, simple additive weighting (SAW) and multiple criteria decision making (MCDM) techniques are leveraged to select the optimal VM scheduling strategy across cloudlets in WMAN. Finally, experimental results and evaluations validate our proposed method is both effective and feasible.

中文翻译：

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无线城域网中跨小云的节能虚拟机调度

如今，随着无线通信的发展，由于各种应用部署以及无线城域网（WMAN）客户丰富的服务经验，人们严重依赖移动设备。移动设备的计算资源受到物理尺寸，电池容量等的限制，因此受到限制。为了解除资源限制，引入了有效的范例cloudlet来承载从移动设备卸载的计算任务。与云计算相比，cloudlets部署得更紧密，为客户提供了更少的任务卸载延迟。当前，分流的任务规模正在增加，这为小云之间的任务实现产生了大量的能量暴露。利用实时虚拟机（VM）迁移技术，可以肯定地减少小云的能耗。但是，跨小云的这种迁移也会降低任务的实现性能。因此，联合优化WMAN中的Cloudlet管理的执行性能和能耗仍然是一个挑战。为了克服上述挑战，本文提出了一种新颖的虚拟机调度方法，以平衡注入时间和能耗。具体来说，通过启发式搜索目标小云中正在运行的计算任务来获得可用迁移策略的集合。然后，利用简单的加性加权（SAW）和多准则决策（MCDM）技术在WMAN中跨小云选择最佳VM调度策略。最后，