Optimization of IoT Routing Based on Machine Learning Techniques. Case Study of Passenger Flow Control in Airport 3.0

The IoT allows objects to be sensed across existing network infrastructure, producing opportunities for more integration of the physical world into computer-based systems, which make our computers nowadays more intelligent. IoT technologies are growing rapidly, creating new challenges especially on the routing side. For that IETF designed a routing protocol for low power and lossy networks RPL to deal with the problems related to power consumption on Wireless Sensors Network. Besides, RPL contains special mechanisms for selecting the path between nodes trying to solve the issue of better control power resources.This research focuses on performance analysis of the selection path mechanisms mentioned previously. Furthermore, we will handle two major parameters: Power Consumption and Packet Delivery Ratio as a considered criterion for this evaluation. We will use different scenario to emulate what we can find in real-world applications. At the end we will propose an approach based on the contribution of machine learning to help us in nodes deployment according to the specification of our airport application that we want to implement.