本科毕业论文提出了一种面向太阳能供电 IoT 网络的两阶段优化框架，重点研究动态任务分配和能量感知的函数配置。开发了 MILP 基准测试和基于 GMM 增强的 Receding Horizon Control 算法，以提升效率并适应波动的能量和计算条件。
Apr 30, 2024
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.
Apr 30, 2024