DocumentCode :
3193075
Title :
Lifetime or energy: Consolidating servers with reliability control in virtualized cloud datacenters
Author :
Wei Deng ; Fangming Liu ; Hai Jin ; Xiaofei Liao ; Haikun Liu ; Li Chen
Author_Institution :
Cluster & Grid Comput. Lab. Sch. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2012
fDate :
3-6 Dec. 2012
Firstpage :
18
Lastpage :
25
Abstract :
Server consolidation using virtualization technologies allow cloud-scale datacenters to improve resource utilization and energy efficiency. However, most existing consolidation strategies solely focused on balancing the tradeoff between service-level-agreements (SLAs) desired by cloud applications and energy costs consumed by hosting servers. With the presence of fluctuating workloads in datacenters, the lifetime and reliability of servers under dynamic power-aware consolidation could be adversely impacted by repeated on-off thermal cycles, wear-and-tear and temperature rise. In this paper, we propose a Reliability-Aware server Consolidation stratEgy, named RACE, to address when and how to perform energy-efficient server consolidation in a reliability-friendly and profitable way. The focus is on the characterization and analysis of this problem as a multi-objective optimization, by developing an utility model that unifies multiple constraints on performance SLAs, reliability factors, and energy costs in a holistic manner. An improved grouping genetic algorithm is proposed to search the global optimal solution, which takes advantage of a collection of reliability-aware resource buffering, and virtual machines-to-servers re-mapping heuristics for generating good initial solutions and improving the convergence rate. Extensive simulations are conducted to validate the effectiveness, scalability and overhead of RACE in improving the overall utility of datacenters while avoiding unprofitable consolidation in the long term - compared with pMapper and PADD strategies for server consolidation.
Keywords :
cloud computing; computer centres; contracts; energy conservation; genetic algorithms; power aware computing; reliability theory; resource allocation; thermal management (packaging); virtual machines; RACE; SLA; cloud applications; convergence rate improvement; datacenter utility improvement; dynamic power-aware consolidation; energy costs; energy-efficient server consolidation; global optimal solution; improved grouping genetic algorithm; multiobjective optimization; profitable approach; reliability control; reliability factors; reliability-aware resource buffering; reliability-aware server consolidation strategy; reliability-friendly approach; repeated on-off thermal cycles; resource utilization; server lifetime; server reliability; service level agreements; temperature rise impact; utility model; virtual machines-to-servers re-mapping heuristics; virtualization technologies; virtualized cloud datacenters; wear-and-tear impact; workload fluctuation; Cloud computing; Clouds; Optimization; Program processors; Reliability; Servers; Temperature; Virtualization; cloud datacenter; consolidation; energy management; live migration; reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4673-4511-8
Electronic_ISBN :
978-1-4673-4509-5
Type :
conf
DOI :
10.1109/CloudCom.2012.6427550
Filename :
6427550
Link To Document :
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