In recent years, the in-orbit service technology of space robot clusters has attracted the attention of various space powers. When the space robot cluster serves the target spacecraft in orbit, the collected target information needs to be transmitted to the central satellite. How to balance the communication power consumption of each node in the cluster is an important research problem. Aiming at the problem of optimal communication power between the space robot cluster and the data hub satellite, a central node selection algorithm (data and data compression ratio prediction，DCP) based on data and compression ratio prediction was proposed in this paper. Since the communication power consumption in the cluster communication is mainly related to the communication distance and communication duration (data volume), the data and compression rate at future times can be predicted based on the movement trajectory of the cluster, thus selecting the optimal central node of the cluster and constructing the communication link. In the experimental simulation, compared to a fixed point, degree centrality, betweenness centrality, and closeness centrality, DCP algorithm can effectively reduce the power consumption of cluster communication, and the error is less than 3% compared with the actual optimal result.
YANG Xuan
,
CHEN Hongyu
. Central node selection strategy of spatial robot cluster based on data and compression ratio prediction[J]. Journal of University of Chinese Academy of Sciences, 2024
, 41(5)
: 695
-704
.
DOI: 10.7523/j.ucas.2023.007
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