Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Dynamic Caching Routing Strategy for LEO Satellite Nodes Based on Gradient Boosting Regression Tree

  • Yang Yang (School of Big Data and Computer Science, Guizhou Normal University) ;
  • Shengbo Hu (School of Big Data and Computer Science, Guizhou Normal University) ;
  • Guiju Lu (School of Mechanical and Electrical Engineering, Guizhou Normal University)
  • Received : 2023.07.11
  • Accepted : 2023.11.30
  • Published : 2024.02.29
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Abstract

A routing strategy based on traffic prediction and dynamic cache allocation for satellite nodes is proposed to address the issues of high propagation delay and overall delay of inter-satellite and satellite-to-ground links in low Earth orbit (LEO) satellite systems. The spatial and temporal correlations of satellite network traffic were analyzed, and the relevant traffic through the target satellite was extracted as raw input for traffic prediction. An improved gradient boosting regression tree algorithm was used for traffic prediction. Based on the traffic prediction results, a dynamic cache allocation routing strategy is proposed. The satellite nodes periodically monitor the traffic load on inter-satellite links (ISLs) and dynamically allocate cache resources for each ISL with neighboring nodes. Simulation results demonstrate that the proposed routing strategy effectively reduces packet loss rate and average end-to-end delay and improves the distribution of services across the entire network.

Keywords

Acknowledgement

This research was funded by the National Natural Science Foundation of China (No. 6156010183), Guizhou Province Education Department Projects of China (KY[2017]031 and KY[2020]007).

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