基于时空关联表征的空天地一体化网络资源精准管控方法

Spatiotemporal Correlation Representation based Precise Resource Management in Space-Air-Ground Integrated Network

空天地一体化网络中,资源分布不均匀且随时间动态变化。传统基于静态资源表征的优化调度方法仅在单个时间片上进行调度优化,资源利用率低,并且在网络变化时需频繁地重新调整策略,带来较大迁移成本。为解决这一问题,提出一种空天地一体化网络资源时空关联表征方法。该方法通过在网络的结构邻域和时序邻域两个维度计算节点注意力表征,实现对空天地一体化网络资源时空关联关系的精准建模。在此基础上,提出基于时空关联表征的网络资源精准映射方法,采用置信域策略梯度优化方法,对算法参数进行自适应学习与优化。

In the space-air-ground integrated network,resources are unevenly distributed and dynamically change over time.Traditional optimization scheduling methods based on static resource representation only optimize scheduling within a single time slot,leading to low resource utilization.Moreover,frequent strategy adjustments are required when the network changes,resulting in significant migra-tion costs.To address this issue,this paper proposed a method for spatiotemporal correlation representation of resources in the space-air-ground integrated network.This method computed node attention representations in both structural neighborhoods and chron-ological neighborhoods,enabled precise modeling of spatiotemporal resource correlations in the space-air-ground integrated network.Based on this,this paper proposed a resource precise embedding method based on spatiotemporal correlation representation,and intro-duced the trust region policy optimization method to adaptively learn and optimize algorithm parameters.