dc.creator | Wu, Jinsong | |
dc.creator | Guo, Song | |
dc.creator | Li, Jie | |
dc.creator | Zeng, Deze | |
dc.date.accessioned | 2017-03-02T14:06:33Z | |
dc.date.available | 2017-03-02T14:06:33Z | |
dc.date.created | 2017-03-02T14:06:33Z | |
dc.date.issued | 2016 | |
dc.identifier | IEEE Systems Journal. Volumen: 10 Número: 3 Páginas: 873-887 | |
dc.identifier | 10.1109/JSYST.2016.2550538 | |
dc.identifier | https://repositorio.uchile.cl/handle/2250/142936 | |
dc.description.abstract | Nowadays, there are two significant tendencies, how to process the enormous amount of data, big data, and how to deal with the green issues related to sustainability and environmental concerns. An interesting question is whether there are inherent correlations between the two tendencies in general. To answer this question, this paper firstly makes a comprehensive literature survey on how to green big data systems in terms of the whole life cycle of big data processing, and then this paper studies the relevance between big data and green metrics and proposes two new metrics, effective energy efficiency and effective resource efficiency in order to bring new views and potentials of green metrics for the future times of big data. | |
dc.language | en | |
dc.rights | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Chile | |
dc.source | IEEE Systems Journal | |
dc.subject | sustainability | |
dc.subject | resource efficiency | |
dc.subject | green revolution | |
dc.subject | energy efficiency (EE) | |
dc.subject | environmental sustainability | |
dc.subject | effective resource efficiency (ERE) | |
dc.subject | effective energy efficiency (EEE) | |
dc.subject | data analytics | |
dc.subject | data storage | |
dc.subject | data communications | |
dc.subject | data acquisition | |
dc.subject | data generation | |
dc.subject | Big data | |
dc.title | Big Data Meet Green Challenges: Greening Big Data | |
dc.type | Artículo de revista | |