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Satellite Observation Mission Resource Scheduling Based on Dynamic Coalition Algorithm.

Shijie Zhai1, Tinghua Zhang1, Hao Chen1

  • 1Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China.

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|November 27, 2025
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Summary
This summary is machine-generated.

This study introduces a dynamic coalition algorithm for satellite observation missions, improving task completion and resource utilization. The novel approach enhances system sustainability and efficiency in complex, dynamic environments.

Keywords:
dynamic coalition algorithmfive-dimensional evaluationresource schedulingsatellite observation missionsimulated annealing optimization

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Area of Science:

  • Computer Science
  • Aerospace Engineering
  • Operations Research

Background:

  • Satellite observation missions face challenges due to heterogeneous ground station resources.
  • Dynamic task environments require adaptive resource scheduling solutions.

Purpose of the Study:

  • To propose a resource scheduling method for satellite observation missions using a dynamic coalition algorithm.
  • To enhance system sustainability and optimize resource utilization in dynamic task scenarios.

Main Methods:

  • Developed a five-dimensional evaluation system (spatial proximity, energy, integrity, load balancing, continuous observation).
  • Integrated an improved simulated annealing algorithm for global optimization of coalition structure.
  • Designed a demand-based energy allocation strategy.

Main Results:

  • Achieved a 93.8% task completion rate and 85.7% resource utilization rate.
  • Demonstrated a low energy consumption standard deviation (18.7) and rapid convergence (45 iterations).
  • Outperformed greedy, particle swarm, and genetic algorithms in experimental comparisons.

Conclusions:

  • The dynamic coalition algorithm offers significant improvements in efficiency and sustainability for satellite mission scheduling.
  • Innovative contributions include a dynamic energy allocation model, a hybrid simulated annealing framework, and integrated evaluation/coalition mechanisms.
  • Provides a robust solution for task scheduling in wireless sensor networks within complex, dynamic environments.