Data generation has increased drastically over the past few years. Processing large amounts of data requires huge compute and storage infrastructures, which consume substantial amounts of energy. Moreover, another important aspect to consider is that more and more the data is analyzed on-board battery operated mobile devices like smart-phones and sensors. Therefore, data processing techniques are required to operate while meeting resource constraints such as memory and power to prolong a mobile device network's lifetime. This chapter reviews representative methods used for energy efficient Big Data analysis, providing first a generic overview of the issue of energy conservation and then presenting a more detailed analysis of the issue of energy efficiency in mobile and sensor networks.
Energy Efficiency in Big Data Analysis
Carmela Comito
2018
Abstract
Data generation has increased drastically over the past few years. Processing large amounts of data requires huge compute and storage infrastructures, which consume substantial amounts of energy. Moreover, another important aspect to consider is that more and more the data is analyzed on-board battery operated mobile devices like smart-phones and sensors. Therefore, data processing techniques are required to operate while meeting resource constraints such as memory and power to prolong a mobile device network's lifetime. This chapter reviews representative methods used for energy efficient Big Data analysis, providing first a generic overview of the issue of energy conservation and then presenting a more detailed analysis of the issue of energy efficiency in mobile and sensor networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


