# Distributed Coordination of Space-Ground Multiresources for Remote Sensing Missions
## 4 Distributed Coordinated Resource Scheduling Algorithm Design Based on ADMM
### Algorithm Implementation
With the coordination of the DRS systems and RSS systems, the DCRS scheme can well utilize the degree of freedom to avoid the collisions of relay resources, while NCRS cannot due to the lack of global information. Figure 5: Total working time of the DRSs versus the number of mission requests per RSS system. Figure 6: Number of successfully scheduled missions versus the length of feasible scheduling window. ## 6 Conclusions

This paper studies a distributed resource scheduling method to realize the coordination of space-ground multiresources for remote sensing missions. Compared with the centralized resource scheduling method, our method requires no extra coordination center added in the heterogeneous satellite systems. Moreover, it only requires very limited link scheduling information interchange among different satellite systems. Other local information is well-preserved. Therefore, the proposed method is much easier to apply to real systems than centralized coordinated scheduling methods. Simulation results shows that the number of completed missions of the proposed algorithm is improved about 24% compared with NCRS, and it achieves no less than 96% of the centralized coordinated scheduling algorithm. However, as the proposed algorithm is realized by iteration, it requires more computation time and times of information exchanging among the RRS and DRS systems than the noncoordinated scheduling algorithm and centralized coordinated scheduling algorithm. Therefore, it is only suitable for the offline schedule of the none-mergency missions, which can be planned in advance by the OCCs on the ground, and cannot be employed in online schedules for emergency missions. In our future work, we will study the distributed online coordinated scheduling algorithm for emergency remote sensing missions. Conceptualization, R.L. ; methodology, R.L. and W.W.; simulation, X.D. ; validation, W.G. ; formal analysis, R.L. and W.W.; writing--original draft preparation, X.D. ; writing--review and editing, R.L., W.W. and W.G. ; visualization, X.D. ; supervision, W.G. All authors have read and agreed to the published version of the manuscript. Figure 8: Total working time of the DRSs versus the length of feasible scheduling windows. Figure 7: Total working time of the ground stations versus the length of feasible scheduling windows. **Funding:** This research was funded by the National Natural Science Foundation of China (No. 62001349), Natural Science Basic Research Program of Shaanxi (No. 2023-JC-YB-566, No. 2023-JC-YB-542), China Postdoctoral Science Foundation (No. 2018M633462), Key Research and Development Program in Shaanxi Province of China (No. 2021 GY-066), Young Talent fund of University Association for Science and Technology in Shaanxi, China (No. 20200112), Postdoctoral Foundation in Shaanxi Province of China (No. 2018 BSHEDZZ47). **Data Availability Statement:** No new data were created or analyzed in this study. **Conflicts of Interest:** The authors declare no conflict of interest. ## References

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