Efficiency-fairness tradeoff in distributed satellite scheduling.

Area of Science:

• Space Engineering
• Operations Research
• Computer Science

Background:

• Increasing demand for Earth observation satellite services necessitates improved planning solutions.
• Balancing efficiency and fairness is crucial for satellite scheduling, but privacy concerns hinder centralized approaches.
• A distributed scheduling approach is needed to address these challenges.

Purpose of the Study:

• To address the multi-objective optimization problem of distributed scheduling for Earth observation satellites.
• To propose novel algorithms for achieving a balanced trade-off between efficiency and fairness.
• To evaluate the performance of these algorithms in a distributed setting.

Main Methods:

• Developed two novel algorithms for distributed multi-objective optimization.
• Focused on balancing efficiency and fairness in satellite task scheduling.
• Conducted experimental evaluations to analyze algorithm performance.

Main Results:

• Each proposed algorithm demonstrates a distinct trade-off between efficiency and fairness.
• The performance characteristics of the algorithms are dependent on specific problem parameters.
• The study validates the effectiveness of the distributed approach for satellite scheduling.

Conclusions:

• The developed algorithms offer viable solutions for distributed Earth observation satellite scheduling.
• The findings highlight the importance of considering problem-specific parameters when selecting an algorithm.
• This research contributes to more efficient and equitable utilization of satellite resources.