Big Data Meet Green Challenges: Big Data Toward Green Applications

Big data are widely recognized as being one of the most powerful drivers to promote productivity, improve efficiency, and support innovation. It is highly expected to explore the power of big data and turn big data into big values. To answer the interesting question whether there are inherent correlations between the two tendencies of big data and green challenges, a recent study has investigated the issues on greening the whole life cycle of big data systems. This paper would like to discover the relations between the trend of big data era and that of the new generation green revolution through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.

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@articleabstract = "Big data are widely recognized as being one of the most powerful drivers to promote productivity, improve efficiency, and support innovation. It is highly expected to explore the power of big data and turn big data into big values. To answer the interesting question whether there are inherent correlations between the two tendencies of big data and green challenges, a recent study has investigated the issues on greening the whole life cycle of big data systems. This paper would like to discover the relations between the trend of big data era and that of the new generation green revolution through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.",

keywords = "Big data, data analytics, energy efficiency, environmental issues, environmental sustainability, green, green revolution, recyclability, renewable resource, resource efficiency, sustainability, sustainability applications, sustainable environments",

author = "Jinsong Wu and Song Guo and Jie Li and Deze Zeng", year = "2016", month = sep, doi = "10.1109/JSYST.2016.2550530", language = "English", volume = "10", pages = "888--900", journal = "IEEE Systems Journal", issn = "1932-8184", publisher = "IEEE",

Research output : Journal article publication › Journal article › Academic research › peer-review

T1 - Big Data Meet Green Challenges: Big Data Toward Green Applications

N2 - Big data are widely recognized as being one of the most powerful drivers to promote productivity, improve efficiency, and support innovation. It is highly expected to explore the power of big data and turn big data into big values. To answer the interesting question whether there are inherent correlations between the two tendencies of big data and green challenges, a recent study has investigated the issues on greening the whole life cycle of big data systems. This paper would like to discover the relations between the trend of big data era and that of the new generation green revolution through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.

AB - Big data are widely recognized as being one of the most powerful drivers to promote productivity, improve efficiency, and support innovation. It is highly expected to explore the power of big data and turn big data into big values. To answer the interesting question whether there are inherent correlations between the two tendencies of big data and green challenges, a recent study has investigated the issues on greening the whole life cycle of big data systems. This paper would like to discover the relations between the trend of big data era and that of the new generation green revolution through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.

KW - data analytics

KW - energy efficiency

KW - environmental issues

KW - environmental sustainability

KW - green revolution

KW - renewable resource

KW - resource efficiency

KW - sustainability applications

KW - sustainable environments

M3 - Journal article

JO - IEEE Systems Journal

JF - IEEE Systems Journal