A Two-Stage Framework for Static Task–Channel Allocation and Low-Cost Dynamic Reconfiguration Under Temporal-Frequency Constraints

Efficient task–channel allocation in satellite communication networks becomes particularly challenging when tasks are subject to both time and frequency constraints, and when resource failures or environmental changes invalidate an initially feasible allocation. Existing studies often treat static allocation and dynamic adaptation separately, lacking a unified framework that ensures both a low resource fragmentation rate and low reconfiguration cost. This paper proposes a two-stage approach that integrates static task–channel allocation with dynamic reconfiguration. In the static stage, a greedy algorithm is developed to assign tasks to channels under time-window, bandwidth, and conflict-free constraints, aiming to achieve as low a resource fragmentation rate as possible within the heuristic search. When channel failures occur, a heuristic search-based reconfiguration algorithm is proposed to generate a sequence of reconfiguration events that transitions the initial static allocation strategy step by step to a feasible target static allocation strategy, while maintaining constraint satisfaction and an acceptable resource fragmentation rate throughout the process. Comparative experiments on both small-scale and large-scale datasets demonstrate that the unified framework effectively balances allocation quality, low-cost and compact dynamic reconfiguration, and adaptability in dynamic network environments.