DocumentCode
3575439
Title
ECCO: An Integrated Solution for Environment Compatible COmputing Systems
Author
Barone, Giovanni Battista ; Bottalico, Davide ; Boccia, Vania ; Carracciuolo, Luisa
Author_Institution
Univ. of Naples Federico II, Naples, Italy
fYear
2014
Firstpage
545
Lastpage
550
Abstract
Large data centers have costs of implementation and management generally very high and a significant part of these costs are related to energy consumption. In addition, Governments, in the implementation of the Kyoto Protocol, push to adopt in the coming years more responsible behavior towards the environment implementing energy-saving strategies also in the management of big Data Centers. Thus, if some actions to reduce the energy impact on the overall costs for large Data Centers can not be postponed, it is also indispensable to take into account the needs of users that thanks to the use of these resources contribute to the advancement of science in strategic, and generally mission-critical, scientific areas. Here we report the experience made for the realization of a complex and modular system, named ECCO, able to automatically and dynamically redefine the set of active resources of a Data Center with the purpose of drastically reducing the energy costs without "too much" neglecting the needs of users. Some issues related to the deploy and the validation of some components of the ECCO system are reported focusing on the real case study of the S.Co.P.E data center at the University of Naples Federico II.
Keywords
computer centres; environmental legislation; green computing; grid computing; resource allocation; ECCO system; Kyoto protocol; S.Co.P.E data center; University of Naples Federico II; active resources; complex modular system realization; energy consumption; energy cost reduction; energy impact reduction; energy-saving strategies; environment compatible computing systems; implementation cost; integrated solution; large-data centers; management cost; strategic-mission-critical scientific areas; user needs; Actuators; Cooling; Energy consumption; Engines; Resource management; Sensors; Virtualization; adaptive scheduling; cloud computing; distributed computing; energy efficiency; green datacenters; grid computing; resource allocation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Networking and Collaborative Systems (INCoS), 2014 International Conference on
Print_ISBN
978-1-4799-6386-7
Type
conf
DOI
10.1109/INCoS.2014.16
Filename
7057147
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