Fuzzy Logic based model for self-optimizing energy consumption in IoT environment

Energy optimization is essential in IoT environments due to energy constraints for some IoT components. In fact, energy consumption has a direct impact on IoT system lifetime, which represents an important Quality of Service (QoS) parameter for IoT environments. In order to extend the IoT system lifetime, energy consumption optimization should be considered in several IoT components. In this paper, we specify an energy self-optimizing mechanism allowing to minimize data transmission energy consumption of IoT objects. This mechanism enables selecting specific objects to send the desired data while minimizing the energy consumed for the corresponding communication. Our proposal is made of a Mamdani Fuzzy Logic based system considering different IoT environment parameters enabling IoT objects evaluation. In this context, three input parameters (Distance between the IoT object collecting the data and the coordinator, Residual Energy in the IoT object, Precision of the information collected by the IoT object) and a single computed output parameter (IoT object chance) are used in our proposed Fuzzy Logic system. The obtained IoT objects chances enable choosing the best IoT object(s) to retrieve the requested data while maximizing the corresponding IoT system lifetime.