Topology Dynamic of Mega-Constellation Networks
Mega-constellation networks face great challenges in providing broadband reliable communication service. The main obstacle is the highly dynamic network topology. This article focuses on this issue and makes an effort to examine the topology dynamic of mega-constellation from a new perspective. Some metrics derived from complex network theory are presented to describe topology characteristics. Considering the impact of the topology dynamic on routing, the topology dynamic characteristics are then expressed by a newly defined topology correlation of the two adjacent snapshots. Three well-known mega-constellations are used as examples and compared by using these metrics. Simulation results show that fewer nodes need to update routes with the same snapshot length when there is a greater correlation between snapshots. In addition, an isochronic snapshot topology control and routing update scheme (ISTC) is proposed to mitigate the problem of the surging number of snapshots due to the complex dynamics of mega-constellations. The upper and lower bound of the snapshot length are presented. So that, local convergence of routes can be achieved and the number of routing updates are as small as possible within each snapshot. Moreover, a decreasing distance shortest distance (DDSD) access satellite selection algorithm is presented to work with the topology control scheme and reduce the number of satellite handovers. Simulation results show that these methods have advantages in coping with the dynamics of constellation networks.
Authors
- Senbai Zhang (ORCID: https://orcid.org/0000-0001-8579-2251)
- Aijun Liu (ORCID: https://orcid.org/0000-0001-7235-9424)
- Xin Xu (ORCID: https://orcid.org/0000-0003-0795-941X)
Institutions
- PLA Army Engineering University (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1109/jiot.2025.3550920
- Citations
- 3
- Primary Topic
- Cellular Automata and Applications
- Type
- article
- Field-Weighted Citation Impact
- 4.51
Funders
- National Natural Science Foundation of China