Energy-Aware Scheduling Scheme Using Workload-Aware Consolidation Technique in Cloud Data Centres  

云数椐中心基于工作负载整合的能耗感知调度方案（英文）

作　　者：黎红友 王江勇 彭舰 王俊峰 刘唐 

机构地区：[1]School of Computer Science,Sichuan University [2]State Key Laboratory of Network and Switching Technology,Beijing University of Posts and Telecommunications

出　　处：《China Communications》2013年第12期114-124,共11页中国通信（英文版）

基　　金：supported by the Opening Project of State key Laboratory of Networking and Switching Technology under Grant No.SKLNST-2010-1-03;the National Natural Science Foundation of China under Grants No.U1333113,No.61303204;the Sichuan Province seedling project under Grant No.2012ZZ036;the Scientific Research Fund of Sichuan Normal University under Grant No.13KYL06

摘　　要：To reduce energy consumption in cloud data centres,in this paper,we propose two algorithms called the Energy-aware Scheduling algorithm using Workload-aware Consolidation Technique(ESWCT) and the Energyaware Live Migration algorithm using Workload-aware Consolidation Technique(ELMWCT).As opposed to traditional energy-aware scheduling algorithms,which often focus on only one-dimensional resource,the two algorithms are based on the fact that multiple resources(such as CPU,memory and network bandwidth)are shared by users concurrently in cloud data centres and heterogeneous workloads have different resource consumption characteristics.Both algorithms investigate the problem of consolidating heterogeneous workloads.They try to execute all Virtual Machines(VMs) with the minimum amount of Physical Machines(PMs),and then power off unused physical servers to reduce power consumption.Simulation results show that both algorithms efficiently utilise the resources in cloud data centres,and the multidimensional resources have good balanced utilizations,which demonstrate their promising energy saving capability.To reduce energy consumption in cloud data centres, in this paper, we propose two algorithms called the Energy-aware Sched- uling algorithm using Workload-aware Conso- lidation Technique （ESWCT） and the Energy- aware Live Migration algorithm using Work- load-aware Consolidation Technique （ELMWCT）. As opposed to traditional energy-aware sche- duling algorithms, which often focus on only one-dimensional resource, the two algorithms are based on the fact that multiple resources （su- ch as CPU, memory and network bandwidth） are shared by users concurrently in cloud data centres and heterogeneous workloads have diffe- rent resource consumption characteristics. Both algorithms investigate the problem of consoli- dating heterogeneous workloads. They try to execute all Virtual Machines （VMs） with the minimum amount of Physical Machines （PMs）, and then power off unused physical servers to reduce power consumption. Simulation results show that both algorithms efficiently utilise the resources in cloud data centres, and the multi- dimensional resources have good balanced uti- lizations, which demonstrate their promising en- ergy saving capability.

关 键 词：energy-aware scheduling hetero-geneous workloads workload-aware consoli-dation cloud data centres 

分 类 号：TP308[自动化与计算机技术—计算机系统结构]