Congestion-Aware Ant Colony Optimization for Time-Varying Networks in All-Optical Satellite Systems

As the commercialization of terrestrial 6G technology accelerates, ground-based 6G networks impose increasingly stringent requirements on performance metrics such as transmission rates and latency control for backhaul links. Against this backdrop, laser communication has effectively transcended the bandwidth limitations inherent in traditional satellite systems, emerging as a key technological direction in the field of space communication. The advent of all-optical single-wavelength multi-hop networks has further broken through the efficiency bottlenecks associated with electro-optical conversion processes. However, existing path planning algorithms for all-optical single-wavelength networks remain inadequate, struggling to efficiently address network congestion and thereby constraining overall performance enhancement. To address these limitations, this paper proposes a congestion-aware ant colony optimization algorithm. By dynamically sensing real-time network congestion states and optimizing path selection strategies accordingly, the proposed algorithm demonstrates significant optimization effects across three critical dimensions: reducing network congestion, minimizing path hop counts, and controlling transmission costs.