The sub-experiments are (1) automatic configuration/discovery of SDN in wireless IoT sensor networks (2) ML- assisted control and data traffic path discovery experiments (3) GPU and Hadoop cluster assisted experiments for ML algorithms (4) Failure recovery intercity experiments and (5) Scalability experiments The US and the EU teams will provide expertise for experimentation on their respective testbeds Also both teams will integrate machine learning-assisted SDN control into IoT allowing cross-Atlantic experimentation to "stress-test" the project’s novel algorithms
The technologies and approaches we are proposing in this project can have a huge impact on the speed at which IoT service providers can make their infrastructure efficiently evolve with their market evolution In fact the impact of this approach for wireless ad-hoc IoT networking can be extended easily to other IoT device communication platforms (eg MQTT) for a comprehensive solution Furthermore we aim to create exemplary knowledge by performing experimentation on one of the world’s largest and most advanced wireless testbeds located over two continents