Optimizing Task Scheduling for Batteryless IoT Devices with Intermittent Energy

Défense de mémoire de Quentin Franssen

This research explores the design and iterative development of a task scheduler tailored for batteryless IoT devices operating under intermittent energy constraints. The primary objective was to optimize task management while ensuring resilience, energy efficiency, and scalability. Each iteration introduced new features, including dynamic queue management, energy pattern prediction, and fault tolerance, addressing the unique requirements of ultra-low-power IoT devices. A rigorous methodology was employed, combining simulations and profiling tools to evaluate metrics such as execution time, CPU usage, memory consumption, and energy efficiency. Despite limitations, such as the lack of real-world hardware testing, this research provides a strong foundation for future work, offering a robust framework for resilient and energy-efficient IoT systems.

Keywords : batteryless IoT, task scheduling, energy efficiency, fault tolerance, scalability, energy intermittence.}

Contact : Isabelle Daelman - isabelle.daelman@unamur.be
Télecharger : vCal