Undergraduate Thesis - Scheduling in Serverless Computing for Solar-Powered IoT Networks

This undergraduate thesis proposes a two-phase optimization framework for solar-powered IoT networks, focusing on dynamic task allocation and energy-aware function configuration. A MILP benchmark and a GMM-enhanced Receding Horizon Control algorithm were developed to improve efficiency and adapt to fluctuating energy and computation conditions.