An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

Huilong Fan, Zhan Yang, Shimin Wu, Xi Zhang, Jun Long and Limin Liu
Additional contact information
Huilong Fan: School of Computer Science and Engineering, Central South University, Changsha 410075, China
Zhan Yang: Network Resource Management and Trust Evaluation Key Laboratory of Hunan, Changsha 410075, China
Shimin Wu: School of Computer Science and Engineering, Central South University, Changsha 410075, China
Xi Zhang: School of Computer Science and Engineering, Central South University, Changsha 410075, China
Jun Long: Network Resource Management and Trust Evaluation Key Laboratory of Hunan, Changsha 410075, China
Limin Liu: School of Computer Science and Engineering, Central South University, Changsha 410075, China

Mathematics, 2021, vol. 9, issue 24, 1-23

Abstract: To overcome the low timeliness of resource scheduling problems in spatial information networks, we propose a method based on a dynamic reconstruction of resource request queues and the autonomous coordinated scheduling of resources. First, we construct a small satellite network and combine the graph maximum flow theory to solve the link resource planning problem during inter-satellite data transmission. In addition, we design a multi-satellite resource scheduling algorithm with minimal time consumption based on graph theory. The algorithm is based on graph theory to reallocate the resource request queue to satellites with idle processing resources. Finally, we simulate the efficient resource scheduling capability in the spatial information network and empirically compare our approaches against two representative swarm intelligence baseline approaches and show that our approach has significant advantages in terms of performance and time consumption during resource scheduling.

Keywords: collaborative scheduling; spatial information network; resource coordination; genetic algorithm; particle swarm optimization algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/24/3293/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/24/3293/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:24:p:3293-:d:705308

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().