Resource Allocation based on IA for IoT...

The need for IoT networks has increased considerably over the years as they bring together communications technologies to provide secure and flexible connectivity to numerous devices in mission critical and non mission critical applications. The complexity, size, and constraints of IoT networks result in modeling that is difficult to mathematically treat and, consequently, obtaining optimal or near-optimal solutions may not be achieved with the computational resources, energy, quality of experience, and constraints that exist in many applications, especially mission-critical ones. Consequently, the use of artificial intelligence techniques, especially machine learning, becomes of great interest, since they circumvent the difficulty of mathematically dealing with highly complex problems, such as the allocation of communications and energy resources in IoT networks. In IoT networks the data is massive and multidimensional, and therefore machine learning and deep learning can be used for decision making. In this sense, the efficient allocation of communication and energy resources is of paramount importance in order to optimize all the resources involved, especially to reduce the inherent impacts of human action on the environment. The massive application of IoT networks implies not only an increase in energy consumption, but also in energy supply. Therefore, environmental or dedicated energy harvesting is of great interest. The project advances the investigations related to the allocation of communications and energy resources for IoT networks, with the use of artificial intelligence techniques to deal with problems of extremely complex mathematical treatability, within a perspective that contemplates scientific and technological or innovative actions.