Space Information Network Task Planning via Resource Interchange
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing methods for task planning in space information networks fail to effectively manage resource interchange quantitatively, leading to high computational complexity due to discontinuity in network resources and task requirements, and often ignore resource correlations, limiting the network's performance in meeting increasing task demands.
Innovation Solution
A method that initializes basic parameters, constructs resource time-varying graphs, samples feasible resource combinations, calculates conflict relations, and performs large-scale global task planning with local adjustments through resource interchange, transforming the task planning problem into a flow problem in graph theory to reduce complexity and enhance resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resource interchange is used to increase matching freedom between resource combinations and tasks, then resource utilization efficiency is improved, but computational complexity of obtaining the optimal solution is significantly increased
Solution Approach 1:
The patent segments the resource interchange process into two distinct phases: a macroscopic phase that identifies potential interchange opportunities between resource combinations, and a microscopic phase that executes specific resource swaps. This segmentation reduces computational complexity by avoiding exhaustive search of all possible resource combinations, instead focusing computation on localized adjustments around promising solutions.
Solution Approach 2:
The patent introduces quantitative parameters including independence threshold n, maximum iteration count L, and resource combination size m to control the resource interchange process. These parameters allow the system to balance between exploration (finding better solutions) and exploitation (refining current solutions), thereby managing computational complexity while maintaining resource utilization efficiency.
2Adaptability or versatility
If the range of feasible solution space is increased through resource interchange, then matching freedom between resource combinations and tasks is improved, but the complexity of obtaining the optimal solution is significantly increased
Solution Approach 1:
The patent implements dynamic control of the resource interchange process through iterative execution with adaptive termination conditions. The algorithm dynamically adjusts the search space by performing resource swaps only when independence criteria are met, rather than exhaustively evaluating all possible combinations. This dynamic approach maintains adaptability while controlling computational complexity through early termination when convergence is detected.
3Device complexity
If heuristic algorithms are used to split the original combinational optimization problem into several sub-problems, then computational complexity is reduced, but correlation between resources is ignored
Solution Approach 1:
The patent incorporates feedback mechanisms that monitor resource correlations throughout the optimization process. After each resource interchange operation, the algorithm recalculates independence metrics and adjusts subsequent swap decisions based on observed correlations. This feedback loop ensures that resource relationships are continuously considered, preventing the loss of correlation information that occurs with simple problem decomposition.
Data Source
AI summary
Disclosed is a method for task planning of a space information network based on resource interchange. The method includes: initializing basic parameters of the space information network; dividing a planning horizon into K time slots of equal length, and constructing a resource time-varying graph for the space information network; sampling a feasible resource combination space of each task, and obtaining a candidate resource combination set comprised of the resource combinations with independence greater than or equal to a threshold n; calculating a conflict relation between resource combinations, and constructing a resource combination conflict graph; obtaining a maximum independent set of the resource combination conflict graph to obtain a global planning result; and searching a neighborhood of the global planning result, and completing a local adjustment of a task planning scheme through the resource interchange, to complete the task planning based on characteristics of the resource interchange.