Mitigating the data-deluge by an adequate sampling for low-power systems
Résumé
Today, our digital society exchanges data ows as never it has been the case in the past. The amount of data is incredibly large and the future promises that not only human will exchange digital data but also technological equipment, robots, etc. We are close to open the door of the internet of things. This data orgy wastes a lot of energy and contributes to a non-ecological approach of our digital life. Indeed, Internet and the new technologies consume about 10It already exists design solutions to enhance the energetic performances of the electronic systems and circuits, of the computers and their mobile applications: a lot of techniques and also a lot of publications! Nevertheless, another way to reduce energy is to rethink the sampling techniques and digital processing chains. Considering that our digital life is dictated by the Shannon theory, we produce more digital data than expected, more than necessary. Indeed, useless data produce more computation, more storage, more communications and also more power consumption. If we disregard the Shannon theory, we can discover new sampling and processing techniques. A small set of ideas is given through examples such as lters, pattern recognition techniques, etc. but the Pandoras Box has to be opened to drastically reduce the useless data and mathematicians probably have a key role to play in this revolution. This study is supported by the Persyval-lab project.