In this page, we present the source codes of the following papers:
Machine Learning Based Task Distribution in Heterogeneous Fog-Cloud Environments. FCSTD: Fog-Cloud Smart Task Distribution by Exploiting the Artificial Neural Networks.
In our experiments, the case study is a WBSN (wireless body sensor network) based delay-sensitive healthcare applications that is produced by "Rayan Tahlil Sepahan" company. This application is responsible to monitor the health status of workers in specific working environments with a high level of heat stress, by estimation of different parameters such as sweat rate and body temperature. As an advantage, utilization of this applications provides the feasibility of preparation of specific working plans for the workers, aiming to keep them healthy in the working environment..
We developed a training algorithms in matlab, in order to train the neural networks for predecting the size of results and the response times of the generated tasks.and the data sets are accessible here.
The source code of FCSTD and MLTD have been also uploaded on github.
Machine Learning Based Task Distribution in Heterogeneous Fog-Cloud Environments, SoftCom2020, Hvar, Croatia, 2020. FCSTD: Fog-Cloud Smart Task Distribution by Exploiting the Artificial Neural Networks, Networks of the Future (NoF2020), Bordeaux, France, 2020.
