Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing

被引:1776
作者
Beloglazov, Anton [1 ]
Abawajy, Jemal [2 ]
Buyya, Rajkumar [1 ]
机构
[1] Univ Melbourne, Dept Comp Sci & Software Engn, Cloud Comp & Distributed Syst CLOUDS Lab, Melbourne, Vic 3010, Australia
[2] Deakin Univ, Sch Informat Technol, Pervas Comp & Networks Res Grp, Melbourne, Vic, Australia
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2012年 / 28卷 / 05期
基金
欧盟地平线“2020”;
关键词
Energy efficiency; Green IT; Cloud computing; Resource management; Virtualization; Dynamic consolidation; ENVIRONMENTS;
D O I
10.1016/j.future.2011.04.017
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Cloud computing offers utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of electrical energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only minimize operational costs but also reduce the environmental impact. In this paper, we define an architectural framework and principles for energy-efficient Cloud computing. Based on this architecture, we present our vision, open research challenges, and resource provisioning and allocation algorithms for energy-efficient management of Cloud computing environments. The proposed energy-aware allocation heuristics provision data center resources to client applications in a way that improves energy efficiency of the data center, while delivering the negotiated Quality of Service (QoS). In particular, in this paper we conduct a survey of research in energy-efficient computing and propose: (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering QoS expectations and power usage characteristics of the devices; and (c) a number of open research challenges, addressing which can bring substantial benefits to both resource providers and consumers. We have validated our approach by conducting a performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant cost savings and demonstrates high potential for the improvement of energy efficiency under dynamic workload scenarios. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:755 / 768
页数:14
相关论文
共 39 条
[1]  
[Anonymous], 2010, P 2010 INT C EN EFF
[2]  
[Anonymous], P ANN C USENIX ANN T
[3]  
[Anonymous], P 11 IFIP IEEE INT N
[4]  
[Anonymous], 2010, Proceedings of the 7th international conference on Autonomic computing, ICAC '10
[5]  
[Anonymous], 2005, P 2 C S NETW SYST DE
[6]   A View of Cloud Computing [J].
Armbrust, Michael ;
Fox, Armando ;
Griffith, Rean ;
Joseph, Anthony D. ;
Katz, Randy ;
Konwinski, Andy ;
Lee, Gunho ;
Patterson, David ;
Rabkin, Ariel ;
Stoica, Ion ;
Zaharia, Matei .
COMMUNICATIONS OF THE ACM, 2010, 53 (04) :50-58
[7]  
Barham P., 2003, P 19 ACM S OP SYST P, P164
[8]  
Buyya R., 2010, ENERGY EFFICIENT MAN
[9]   Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility [J].
Buyya, Rajkumar ;
Yeo, Chee Shin ;
Venugopal, Srikumar ;
Broberg, James ;
Brandic, Ivona .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2009, 25 (06) :599-616
[10]  
Calheiros R.N., 2009, P 38 INT C PAR PROC