ATTENTION/WARNING - NE PAS DÉPOSER ICI/DO NOT SUBMIT HERE

Ceci est la version de TEST de DIAL.mem. Veuillez ne pas soumettre votre mémoire sur ce site mais bien à l'URL suivante: 'https://thesis.dial.uclouvain.be'.
This is the TEST version of DIAL.mem. Please use the following URL to submit your master thesis: 'https://thesis.dial.uclouvain.be'.
 

Doing large-scale computations on an Internet of Things network

(2020)

Files

Banken_15271400_Xanthos_04881400_2020.pdf
  • Open access
  • Adobe PDF
  • 7.28 MB

Details

Supervisors
Faculty
Degree label
Abstract
As you may notice, the Internet-of-Things devices are everywhere: in our factories, in our cities and in our houses. The challenge of tomorrow will be to store and process data generated by these devices. In this master thesis, we tried to tackle this challenge. We implemented a MapReduce algorithm designed to run on the extreme edge of the network. With the edge computing, the IoT devices can exchange, store and process data without depending on an external infrastructure. As part of this master thesis, we developed a resilient MapReduce algorithm that work in a peer-to-peer network composed of IoT devices.