An Energy-Efficient Task Scheduling Heuristic Algorithm Without Virtual Machine Migration in Real-Time Cloud Environments
An Energy-Efficient Task Scheduling Heuristic Algorithm Without Virtual Machine Migration in Real-Time Cloud Environments
复制标题
实时云环境中无需虚拟机迁移的节能任务调度启发式算法
DOI：
10.1007/978-3-319-46298-1_6
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Xiao
中科院分区：
文献类型：
--
作者：
Yi Zhang;Liuhua Chen;Haiying Shen;Xiao
降低能耗已成为云计算中心的重要任务。云数据中心中许多现有的调度方法试图将虚拟机（VM）整合到最少数量的物理机（PM），从而最大限度地减少能耗。虚拟机实时迁移技术用于动态地将虚拟机整合到尽可能少的PM;然而，它引入了高迁移开销。此外，现有方法通常不考虑成本因素，这将导致云用户的支付成本较高。在本文中，我们的目标是实现云提供商的节能和云用户的支付节省，同时，不引入VM迁移开销，不影响用户任务的最后期限保证。由于某些任务的截止日期相对宽松，我们可以通过主动推迟任务而不唤醒新的PM来进一步降低能耗。在本文中，我们提出了一个启发式的任务调度算法，称为能量和截止日期意识与非迁移调度（EDA-NMS）算法。EDA-NMS利用任务期限的宽松性，并试图推迟执行具有宽松期限的任务，以避免唤醒新的PM。EDA-NMS在确定VM即时类型时，选择刚好能够保证任务期限的即时类型，以降低用户支付成本。大量的实验结果表明，我们的算法比其他现有的算法更好地实现能源效率，而不引入VM迁移开销和不妥协的最后期限保证。
Reducing energy consumption has become an important task in cloud datacenters. Many existing scheduling approaches in cloud datacenters try to consolidate virtual machines (VMs) to the minimum number of physical machines (PMs) and hence minimize the energy consumption. VM live migration technique is used to dynamically consolidate VMs to as few PMs as possible; however, it introduces high migration overhead. Furthermore, the cost factor is usually not taken into account by existing approaches, which will lead to high payment cost for cloud users. In this paper, we aim to achieve energy reduction for cloud providers and payment saving for cloud users, and at the same time, without introducing VM migration overhead and without compromising deadline guarantees for user tasks. Motivated by the fact that some of the tasks have relatively loose deadlines, we can further reduce energy consumption by proactively postponing the tasks without waking up new PMs. In this paper, we propose a heuristic task scheduling algorithm called Energy and Deadline Aware with Non-Migration Scheduling (EDA-NMS) algorithm. EDA-NMS exploits the looseness of task deadlines and tries to postpone the execution of the tasks that have loose deadlines in order to avoid waking up new PMs. When determining the VM instant types, EDA-NMS selects the instant types that are just sufficient to guarantee task deadline to reduce user payment cost. The results of extensive experiments show that our algorithm performs better than other existing algorithms on achieving energy efficiency without introducing VM migration overhead and without compromising deadline guarantees.