IoT systems have been massively infiltrating our everyday's life for various applications. One of the main constraints inhibiting the further development of these applications is the limited autonomy of present day batteries. Moreover, energy sustainability is a crucial requirement for systems employed in critical mission applications. A widely used approach to increase the autonomy of IoT systems is the use of renewable sources of energy such as solar, wind, heat, and others to power the devices. For instance, one of the most widespread solutions for wireless sensor nodes is the use of solar panels, which can provide reasonable power input. Their efficiency is determined by the panel's material that defines the conversion efficiency.
Renewable sources of energy are too erratic to provide complete system reliability unless over-dimensioned. In reality, energy supply is often limited, which causes the need for adaption of the node operational strategy to ensure the functional reliability of the system. However, the unreliable nature of renewable energy causes several challenges, which we address in this work. In particular, this thesis investigates the effect of battery imperfections caused by inner diffusion processes in the battery on the energy harvesting wireless device operation and effective energy-balancing strategies for different scenarios and system types.
We propose 1) the transmission strategy, that takes into account the battery properties (leakage, charge recovery, deep discharge, etc.), and reduces the data losses and discharge events; 2) adaptive sampling algorithms, that balances the erratic energy arrivals, validated on the industrial data-logger powered by a solar panel; and 3) energy cooperation in WSN and Smart City contexts. We also focus on critical-mission IoT systems, where the freshness of delivered packets to the monitoring node by the information sources (communication nodes) is the important parameter to be tracked. In this context, we set the objective of age of information minimization taking into account the battery constraints, asymmetry in reliability of information sources, and stability of energy arrivals, that is, the energy harvesting rate.
This array of strategies covers a wide range of applications, scenarios, and requirements. For instance, they can be applied to a smart city represented as a large system of interconnected smart services, or a WSN employed for critical mission applications. We demonstrated that the knowledge of battery and environmental characteristics, and the asymmetric properties of a system is beneficial for designing transmission/sensing strategies
