Co-Optimization of Satellite Wake-Up and Routing for Lifetime and Delay Balance in LEO Constellations

Traditional routing algorithms in low Earth orbit (LEO) satellite networks optimize performance metrics such as delay but are often energy-unaware, leading to constellation energy imbalance and connection lifetime reduction. To address this, we propose a Simulated Annealing-based Hierarchical Satellite Optimizer (SA-HSO), i.e., a hierarchical framework that co-optimizes total service delay and satellite battery lifetime. Specifically, our proposed SA-HSO first formulates an equivalent objective function to minimize the weighted sum of delay and lifetime consumption. Then, it employs an upper-level simulated annealing algorithm to dynamically select the number and set of active satellites, coupled with a lower-level routing optimizer. Simulations show that SA-HSO reduces the normalized objective value by 41.5% and 66.7% compared to the greedy and random activation schemes, respectively. Meanwhile, it improves the energy balance by 33.4% and 48.3%, respectively. Our method effectively balances the energy use and delay reduction, while achieving sustained constellation operation with 99% service reliability.